Sentiment analysis is inevitable in current era. Internet is growing day-by-day. Now-a-days everything is online. We can shop, buy, and sell online. People can give feedbacks / opinions on the internet. Customers can compare among various products by analyzing the product reviews. As more and more people from different age groups and languages are becoming new internet users, we need it in regional languages. Till date most of the work related to sentiment analysis has been done in English language. But when it comes to Indian languages, not much research has done except for few languages. This paper mainly focuses on performing sentiment analysis in one of the Indian languages i.e. Marathi.
A survey on sentiment analysis and opinion miningeSAT Journals
Abstract Sentiment analysis is a machine learning approach in which machines analyze and classify the human’s sentiments, emotions, opinions etc about some topic which are expressed in the form of either text or speech. The textual data available in the web is increasing day by day. In order to enhance the sales of a product and to improve the customer satisfaction, most of the on-line shopping sites provide the opportunity to customers to write reviews about products. These reviews are large in number and to mine the overall sentiment or opinion polarity from all of them, sentiment analysis can be used. Manual analysis of such large number of reviews is practically impossible. Therefore automated approach of a machine has significant role in solving this hard problem. The major challenge of the area of Sentiment analysis and Opinion mining lies in identifying the emotions expressed in these texts. This literature survey is done to study the sentiment analysis problem in-depth and to familiarize with other works done on the subject. Index Terms: Sentiment Analysis, Opinion Mining, Cross Domain Sentiment Analysis
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
"Knowing about the user’s feedback can come to a greater aid in knowing the user as well as improving the organization. Here an example of student’s data is taken for study purpose. Analyzing the student feedback will help to help to address student related problems and help to make teaching more student oriented. Prashali S. Shinde | Asmita R. Kanase | Rutuja S. Pawar | Yamini U. Waingankar ""Sentiment Analysis of Feedback Data"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Fostering Innovation, Integration and Inclusion Through Interdisciplinary Practices in Management , March 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23090.pdf
Paper URL: https://www.ijtsrd.com/other-scientific-research-area/other/23090/sentiment-analysis-of-feedback-data/prashali--s-shinde"
Artificial intelligence involves two basic ideas. First, it involves studying the thought processes of human beings. Second, it deals with representing those processes via machines (like computers, robots, etc.). Artificial intelligence (AI) technologies and techniques have useful purposes in every domain of mental health care including clinical decision-making, treatments, assessment, self-care, mental health care management and more. This application involves an AI based fuzzy expert system which helps the students to give a basic idea or insight of possible career opportunities, to enable them to move forward towards the path most suitable for them in all respects. This project will give a personal aid to the students taking into consideration, the student’s interest and aptitude test result. The fuzzy expert in our project will choose accurate careers for the user accordingly.
Insights to Problems, Research Trend and Progress in Techniques of Sentiment ...IJECEIAES
The research-based implementations towards Sentiment analyses are about a decade old and have introduced many significant algorithms, techniques, and framework towards enhancing its performance. The applicability of sentiment analysis towards business and the political survey is quite immense. However, we strongly feel that existing progress in research towards Sentiment Analysis is not at par with the demand of massively increasing dynamic data over the pervasive environment. The degree of problems associated with opinion mining over such forms of data has been less addressed, and still, it leaves the certain major scope of research. This paper will brief about existing research trends, some important research implementation in recent times, and exploring some major open issues about sentiment analysis. We believe that this manuscript will give a progress report with the snapshot of effectiveness borne by the research techniques towards sentiment analysis to further assist the upcoming researcher to identify and pave their research work in a perfect direction towards considering research gap.
A survey on sentiment analysis and opinion miningeSAT Journals
Abstract Sentiment analysis is a machine learning approach in which machines analyze and classify the human’s sentiments, emotions, opinions etc about some topic which are expressed in the form of either text or speech. The textual data available in the web is increasing day by day. In order to enhance the sales of a product and to improve the customer satisfaction, most of the on-line shopping sites provide the opportunity to customers to write reviews about products. These reviews are large in number and to mine the overall sentiment or opinion polarity from all of them, sentiment analysis can be used. Manual analysis of such large number of reviews is practically impossible. Therefore automated approach of a machine has significant role in solving this hard problem. The major challenge of the area of Sentiment analysis and Opinion mining lies in identifying the emotions expressed in these texts. This literature survey is done to study the sentiment analysis problem in-depth and to familiarize with other works done on the subject. Index Terms: Sentiment Analysis, Opinion Mining, Cross Domain Sentiment Analysis
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
"Knowing about the user’s feedback can come to a greater aid in knowing the user as well as improving the organization. Here an example of student’s data is taken for study purpose. Analyzing the student feedback will help to help to address student related problems and help to make teaching more student oriented. Prashali S. Shinde | Asmita R. Kanase | Rutuja S. Pawar | Yamini U. Waingankar ""Sentiment Analysis of Feedback Data"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Fostering Innovation, Integration and Inclusion Through Interdisciplinary Practices in Management , March 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23090.pdf
Paper URL: https://www.ijtsrd.com/other-scientific-research-area/other/23090/sentiment-analysis-of-feedback-data/prashali--s-shinde"
Artificial intelligence involves two basic ideas. First, it involves studying the thought processes of human beings. Second, it deals with representing those processes via machines (like computers, robots, etc.). Artificial intelligence (AI) technologies and techniques have useful purposes in every domain of mental health care including clinical decision-making, treatments, assessment, self-care, mental health care management and more. This application involves an AI based fuzzy expert system which helps the students to give a basic idea or insight of possible career opportunities, to enable them to move forward towards the path most suitable for them in all respects. This project will give a personal aid to the students taking into consideration, the student’s interest and aptitude test result. The fuzzy expert in our project will choose accurate careers for the user accordingly.
Insights to Problems, Research Trend and Progress in Techniques of Sentiment ...IJECEIAES
The research-based implementations towards Sentiment analyses are about a decade old and have introduced many significant algorithms, techniques, and framework towards enhancing its performance. The applicability of sentiment analysis towards business and the political survey is quite immense. However, we strongly feel that existing progress in research towards Sentiment Analysis is not at par with the demand of massively increasing dynamic data over the pervasive environment. The degree of problems associated with opinion mining over such forms of data has been less addressed, and still, it leaves the certain major scope of research. This paper will brief about existing research trends, some important research implementation in recent times, and exploring some major open issues about sentiment analysis. We believe that this manuscript will give a progress report with the snapshot of effectiveness borne by the research techniques towards sentiment analysis to further assist the upcoming researcher to identify and pave their research work in a perfect direction towards considering research gap.
Methods for Sentiment Analysis: A Literature Studyvivatechijri
Sentiment analysis is a trending topic, as everyone has an opinion on everything. The systematic
study of these opinions can lead to information which can prove to be valuable for many companies and
industries in future. A huge number of users are online, and they share their opinions and comments regularly,
this information can be mined and used efficiently. Various companies can review their own product using
sentiment analysis and make the necessary changes in future. The data is huge and thus it requires efficient
processing to collect this data and analyze it to produce required result.
In this paper, we will discuss the various methods used for sentiment analysis. It also covers various techniques
used for sentiment analysis such as lexicon based approach, SVM [10], Convolution neural network,
morphological sentence pattern model [1] and IML algorithm. This paper shows studies on various data sets
such as Twitter API, Weibo, movie review, IMDb, Chinese micro-blog database [9] and more. The paper shows
various accuracy results obtained by all the systems.
Question and Answer System (QAS) are some of the many challenges for natural language understanding and interfaces. In this paper we have develop a new scoring mathematical model that works on the five types of questions. The question text failures are first extracted and a score is found based on its structure with respect to its template structure and then answer score is calculated again the question as well as paragraph. A name entity recognizer and a Part of Speech tagger are applied on each of these words to encode necessary of information. After that the text to finally reach at the index of the most probable answer with respect to question. In this the entropy algorithm is used to find the exact answer.
Machine Learning Techniques with Ontology for Subjective Answer Evaluationijnlc
Computerized Evaluation of English Essays is performed using Machine learning techniques like Latent
Semantic Analysis (LSA), Generalized LSA, Bilingual Evaluation Understudy and Maximum Entropy.
Ontology, a concept map of domain knowledge, can enhance the performance of these techniques. Use of
Ontology makes the evaluation process holistic as presence of keywords, synonyms, the right word
combination and coverage of concepts can be checked. In this paper, the above mentioned techniques are
implemented both with and without Ontology and tested on common input data consisting of technical
answers of Computer Science. Domain Ontology of Computer Graphics is designed and developed. The
software used for implementation includes Java Programming Language and tools such as MATLAB,
Protégé, etc. Ten questions from Computer Graphics with sixty answers for each question are used for
testing. The results are analyzed and it is concluded that the results are more accurate with use of
Ontology.
A Survey on Sentiment Analysis and Opinion MiningIJSRD
In Today’s world, the social media has given web users a place for expressing and sharing their thoughts and opinions on different topics or events. For this purpose, the opinion mining has gained the importance. Sentiment classification and Opinion Mining is the study of people’s opinion, emotions, attitude towards the product, services, etc. Sentiment Analysis and Opinion Mining are the two interchangeable terms. There are various approaches and techniques exist for Sentiment Analysis like Naïve Bayes, Decision Trees, Support Vector Machines, Random Forests, Maximum Entropy, etc. Opinion mining is a useful and beneficial way to scientific surveys, political polls, market research and business intelligence, etc. This paper presents a literature review of various techniques used for opinion mining and sentiment analysis.
QUESTION ANSWERING SYSTEM USING ONTOLOGY IN MARATHI LANGUAGEijaia
Humans are always in a quest to extract information related to some topic or entity. Question answering system helps user to find the precise answer of the question articulated in natural language. Question answering system provides explicit, concise and accurate answer to user questions rather than providing set of relevant documents or web pages as answers as most of the information retrieval system does. The paper proposes question answering system for Marathi natural language by using concept of ontology as a formal representation of knowledge base for extracting answers. Ontology is used to express domain specific knowledge about semantic relations and restrictions in the given domains. The ontologies are developed with the help of domain experts and the query is analyzed both syntactically and semantically. The results obtained here are accurate enough to satisfy the query raised by the user. The level of accuracy is enhanced since the query is analyzed semantically.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
COMPARISON INTELLIGENT ELECTRONIC ASSESSMENT WITH TRADITIONAL ASSESSMENT FOR ...cseij
In education, the use of electronic (E) examination systems is not a novel idea, as E-examination systems
have been used to conduct objective assessments for the last few years. This research deals with randomly
designed E-examinations and proposes an E-assessment system that can be used for subjective questions.
This system assesses answers to subjective questions by finding a matching ratio for the keywords in
instructor and student answers.
Opinion Mining and Improvised Algorithm for Feature Reduction in Sentiment An...IJERA Editor
Nowadays organisations use the power of the web to analyse the review of the product by customer. The organisation cannot trust star based reviews because it can be faked by robots. That is why textual review is preferable. Opinion mining is used to find the approximate sentiment of the review. Sentiment analysis is a part of opinion mining which helps an organisation to get valuable feedback of the product by extracting the polarity of reviews. The review of a product may be used to improve productivity of the organisation as it could improve its product's features based on reviews. It provides us ways to analyse a given review. In our review paper, we have emphasised on the content based analysis of the review rather than deciding the contextual polarity by its topic. We have reached to our proposed algorithm by referring to BoPang and LillianLee’ s [2] paper and Tirath Prasad Sahu and Sanjeev Ahuja’ s [3] paper.
The sarcasm detection with the method of logistic regressionEditorIJAERD
The prediction analysis is approach which may predict future possibilities. This research work is based on the
sarcasm detection from the text data. In the previous time SVM classification is applied for the sarcasm detection. The SVM
classifier classifies data based on the hyper plane which give low accuracy. To improve accuracy for sarcasm detection
logistic regression is applied during this work. The existing and proposed techniques are implemented in python and results
are analysed in terms of accuracy, execution time. The proposed approach has high accuracy and low execution time as
compared to SVM classifier for sarcasm detection.
Senti-Lexicon and Analysis for Restaurant Reviews of Myanmar TextIJAEMSJORNAL
Social media has just become as an influential with the rapidly growing popularity of online customers reviews available in social sites by using informal languages and emoticons. These reviews are very helpful for new customers and for decision making process. Sentiment analysis is to state the feelings, opinions about people’s reviews together with sentiment. Most of researchers applied sentiment analysis for English Language. There is no research efforts have sought to provide sentiment analysis of Myanmar text. To tackle this problem, we propose the resource of Myanmar Language for mining food and restaurants’ reviews. This paper aims to build language resource to overcome the language specific problem and opinion word extraction for Myanmar text reviews of consumers. We address dictionary based approach of lexicon-based sentiment analysis for analysis of opinion word extraction in food and restaurants domain. This research assesses the challenges and problem faced in sentiment analysis of Myanmar Language area for future.
Mining of product reviews at aspect levelijfcstjournal
Today’s world is a world of Internet, almost all work can be done with the help of it, from simple mobile
phone recharge to biggest business deals can be done with the help of this technology. People spent their
most of the times on surfing on the Web; it becomes a new source of entertainment, education,
communication, shopping etc. Users not only use these websites but also give their feedback and
suggestions that will be useful for other users. In this way a large amount of reviews of users are collected
on the Web that needs to be explored, analyse and organized for better decision making. Opinion Mining or
Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the
user’s views or opinions explained in the form of positive, negative or neutral comments and quotes
underlying the text. Aspect based opinion mining is one of the level of Opinion mining that determines the
aspect of the given reviews and classify the review for each feature. In this paper an aspect based opinion
mining system is proposed to classify the reviews as positive, negative and neutral for each feature.
Negation is also handled in the proposed system. Experimental results using reviews of products show the
effectiveness of the system.
Methods for Sentiment Analysis: A Literature Studyvivatechijri
Sentiment analysis is a trending topic, as everyone has an opinion on everything. The systematic
study of these opinions can lead to information which can prove to be valuable for many companies and
industries in future. A huge number of users are online, and they share their opinions and comments regularly,
this information can be mined and used efficiently. Various companies can review their own product using
sentiment analysis and make the necessary changes in future. The data is huge and thus it requires efficient
processing to collect this data and analyze it to produce required result.
In this paper, we will discuss the various methods used for sentiment analysis. It also covers various techniques
used for sentiment analysis such as lexicon based approach, SVM [10], Convolution neural network,
morphological sentence pattern model [1] and IML algorithm. This paper shows studies on various data sets
such as Twitter API, Weibo, movie review, IMDb, Chinese micro-blog database [9] and more. The paper shows
various accuracy results obtained by all the systems.
Question and Answer System (QAS) are some of the many challenges for natural language understanding and interfaces. In this paper we have develop a new scoring mathematical model that works on the five types of questions. The question text failures are first extracted and a score is found based on its structure with respect to its template structure and then answer score is calculated again the question as well as paragraph. A name entity recognizer and a Part of Speech tagger are applied on each of these words to encode necessary of information. After that the text to finally reach at the index of the most probable answer with respect to question. In this the entropy algorithm is used to find the exact answer.
Machine Learning Techniques with Ontology for Subjective Answer Evaluationijnlc
Computerized Evaluation of English Essays is performed using Machine learning techniques like Latent
Semantic Analysis (LSA), Generalized LSA, Bilingual Evaluation Understudy and Maximum Entropy.
Ontology, a concept map of domain knowledge, can enhance the performance of these techniques. Use of
Ontology makes the evaluation process holistic as presence of keywords, synonyms, the right word
combination and coverage of concepts can be checked. In this paper, the above mentioned techniques are
implemented both with and without Ontology and tested on common input data consisting of technical
answers of Computer Science. Domain Ontology of Computer Graphics is designed and developed. The
software used for implementation includes Java Programming Language and tools such as MATLAB,
Protégé, etc. Ten questions from Computer Graphics with sixty answers for each question are used for
testing. The results are analyzed and it is concluded that the results are more accurate with use of
Ontology.
A Survey on Sentiment Analysis and Opinion MiningIJSRD
In Today’s world, the social media has given web users a place for expressing and sharing their thoughts and opinions on different topics or events. For this purpose, the opinion mining has gained the importance. Sentiment classification and Opinion Mining is the study of people’s opinion, emotions, attitude towards the product, services, etc. Sentiment Analysis and Opinion Mining are the two interchangeable terms. There are various approaches and techniques exist for Sentiment Analysis like Naïve Bayes, Decision Trees, Support Vector Machines, Random Forests, Maximum Entropy, etc. Opinion mining is a useful and beneficial way to scientific surveys, political polls, market research and business intelligence, etc. This paper presents a literature review of various techniques used for opinion mining and sentiment analysis.
QUESTION ANSWERING SYSTEM USING ONTOLOGY IN MARATHI LANGUAGEijaia
Humans are always in a quest to extract information related to some topic or entity. Question answering system helps user to find the precise answer of the question articulated in natural language. Question answering system provides explicit, concise and accurate answer to user questions rather than providing set of relevant documents or web pages as answers as most of the information retrieval system does. The paper proposes question answering system for Marathi natural language by using concept of ontology as a formal representation of knowledge base for extracting answers. Ontology is used to express domain specific knowledge about semantic relations and restrictions in the given domains. The ontologies are developed with the help of domain experts and the query is analyzed both syntactically and semantically. The results obtained here are accurate enough to satisfy the query raised by the user. The level of accuracy is enhanced since the query is analyzed semantically.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
COMPARISON INTELLIGENT ELECTRONIC ASSESSMENT WITH TRADITIONAL ASSESSMENT FOR ...cseij
In education, the use of electronic (E) examination systems is not a novel idea, as E-examination systems
have been used to conduct objective assessments for the last few years. This research deals with randomly
designed E-examinations and proposes an E-assessment system that can be used for subjective questions.
This system assesses answers to subjective questions by finding a matching ratio for the keywords in
instructor and student answers.
Opinion Mining and Improvised Algorithm for Feature Reduction in Sentiment An...IJERA Editor
Nowadays organisations use the power of the web to analyse the review of the product by customer. The organisation cannot trust star based reviews because it can be faked by robots. That is why textual review is preferable. Opinion mining is used to find the approximate sentiment of the review. Sentiment analysis is a part of opinion mining which helps an organisation to get valuable feedback of the product by extracting the polarity of reviews. The review of a product may be used to improve productivity of the organisation as it could improve its product's features based on reviews. It provides us ways to analyse a given review. In our review paper, we have emphasised on the content based analysis of the review rather than deciding the contextual polarity by its topic. We have reached to our proposed algorithm by referring to BoPang and LillianLee’ s [2] paper and Tirath Prasad Sahu and Sanjeev Ahuja’ s [3] paper.
The sarcasm detection with the method of logistic regressionEditorIJAERD
The prediction analysis is approach which may predict future possibilities. This research work is based on the
sarcasm detection from the text data. In the previous time SVM classification is applied for the sarcasm detection. The SVM
classifier classifies data based on the hyper plane which give low accuracy. To improve accuracy for sarcasm detection
logistic regression is applied during this work. The existing and proposed techniques are implemented in python and results
are analysed in terms of accuracy, execution time. The proposed approach has high accuracy and low execution time as
compared to SVM classifier for sarcasm detection.
Senti-Lexicon and Analysis for Restaurant Reviews of Myanmar TextIJAEMSJORNAL
Social media has just become as an influential with the rapidly growing popularity of online customers reviews available in social sites by using informal languages and emoticons. These reviews are very helpful for new customers and for decision making process. Sentiment analysis is to state the feelings, opinions about people’s reviews together with sentiment. Most of researchers applied sentiment analysis for English Language. There is no research efforts have sought to provide sentiment analysis of Myanmar text. To tackle this problem, we propose the resource of Myanmar Language for mining food and restaurants’ reviews. This paper aims to build language resource to overcome the language specific problem and opinion word extraction for Myanmar text reviews of consumers. We address dictionary based approach of lexicon-based sentiment analysis for analysis of opinion word extraction in food and restaurants domain. This research assesses the challenges and problem faced in sentiment analysis of Myanmar Language area for future.
Mining of product reviews at aspect levelijfcstjournal
Today’s world is a world of Internet, almost all work can be done with the help of it, from simple mobile
phone recharge to biggest business deals can be done with the help of this technology. People spent their
most of the times on surfing on the Web; it becomes a new source of entertainment, education,
communication, shopping etc. Users not only use these websites but also give their feedback and
suggestions that will be useful for other users. In this way a large amount of reviews of users are collected
on the Web that needs to be explored, analyse and organized for better decision making. Opinion Mining or
Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the
user’s views or opinions explained in the form of positive, negative or neutral comments and quotes
underlying the text. Aspect based opinion mining is one of the level of Opinion mining that determines the
aspect of the given reviews and classify the review for each feature. In this paper an aspect based opinion
mining system is proposed to classify the reviews as positive, negative and neutral for each feature.
Negation is also handled in the proposed system. Experimental results using reviews of products show the
effectiveness of the system.
Opinion mining of movie reviews at document levelijitjournal
The whole world is changed rapidly and using the current technologies Internet becomes an essential
need for everyone. Web is used in every field. Most of the people use web for a common purpose like
online shopping, chatting etc. During an online shopping large number of reviews/opinions are given by
the users that reflect whether the product is good or bad. These reviews need to be explored, analyse and
organized for better decision making. Opinion Mining is a natural language processing task that deals
with finding orientation of opinion in a piece of text with respect to a topic. In this paper a document
based opinion mining system is proposed that classify the documents as positive, negative and neutral.
Negation is also handled in the proposed system. Experimental results using reviews of movies show the
effectiveness of the system.
APPROXIMATE ANALYTICAL SOLUTION OF NON-LINEAR BOUSSINESQ EQUATION FOR THE UNS...mathsjournal
For one dimensional homogeneous, isotropic aquifer, without accretion the governing Boussinesq
equation under Dupuit assumptions is a nonlinear partial differential equation. In the present paper
approximate analytical solution of nonlinear Boussinesq equation is obtained using Homotopy
perturbation transform method(HPTM). The solution is compared with the exact solution. The
comparison shows that the HPTM is efficient, accurate and reliable. The analysis of two important aquifer
parameters namely viz. specific yield and hydraulic conductivity is studied to see the effects on the height
of water table. The results resemble well with the physical phenomena.
FEATURE SELECTION AND CLASSIFICATION APPROACH FOR SENTIMENT ANALYSISmlaij
Sentiment analysis and Opinion mining has emerged as a popular and efficient technique for information retrieval and web data analysis. The exponential growth of the user generated content has opened new horizons for research in the field of sentiment analysis. This paper proposes a model for sentiment analysis of movie reviews using a combination of natural language processing and machine learning approaches. Firstly, different data pre-processing schemes are applied on the dataset. Secondly, the behaviour of twoclassifiers, Naive Bayes and SVM, is investigated in combination with different feature selection schemes to
obtain the results for sentiment analysis. Thirdly, the proposed model for sentiment analysis is extended to
obtain the results for higher order n-grams.
Opinion Mining Techniques for Non-English Languages: An OverviewCSCJournals
The amount of user-generated data on web is increasing day by day giving rise to necessity of automatic tools to analyze huge data and extract useful information from it. Opinion Mining is an emerging area of research concerning with extracting and analyzing opinions expressed in texts. It is a language and domain dependent task having number of applications like recommender systems, review analysis, marketing systems, etc. Early research in the field of opinion mining has concentrated on English language. Many opinion mining tools and linguistic resources have been built for English language. Availability of information in regional languages has motivated researchers to develop tools and resources for non-English languages. In this paper we present a survey on the opinion mining research for non-English languages.
Due to the fast growth of World Wide Web the online communication has increased. In recent times the communication focus has shifted to social networking. In order to enhance the text methods of communication such as tweets, blogs and chats, it is necessary to examine the emotion of user by studying the input text. Online reviews are posted by customers for the products and services on offer at a website portal. This has provided impetus to substantial growth of online purchasing making opinion analysis a vital factor for business development. To analyze such text and reviews sentiment analysis is used. Sentiment analysis is a sub domain of Natural Language Processing which acquires writer’s feelings about several products which are placed on the internet through various comments or posts. It is used to find the opinion or response of the user. Opinion may be positive, negative or neutral. In this paper a review on sentiment analysis is done and the challenges and issues involved in the process are discussed. The approaches to sentiment analysis using dictionaries such as SenticNet, SentiFul, SentiWordNet, and WordNet are studied. Dictionary-based approaches are efficient over a domain of study. Although a generalized dictionary like WordNet may be used, the accuracy of the classifier get affected due to issues like negation, synonyms, sarcasm, etc.
w
Analyzing sentiment system to specify polarity by lexicon-basedjournalBEEI
Currently, sentiment analysis into positive or negative getting more attention from the researchers. With the rapid development of the internet and social media have made people express their views and opinion publicly. Analyzing the sentiment in people views and opinion impact many fields such as services and productions that companies offer. Movie reviewer needs many processing to be prepared to detect emotion, classify them and achieve high accuracy. The difficulties arise due of the structure and grammar of the language and manage the dictionary. We present a system that assigns scores indicating positive or negative opinion to each distinct entity in the text corpus. Propose an innovative formula to compute the polarity score for each word occurring in the text and find it in positive dictionary or negative dictionary we have to remove it from text. After classification, the words are stored in a list that will be used to calculate the accuracy. The results reveal that the system achieved the best results in accuracy of 76.585%.
Sentiment classification aims to detect information such as opinions, explicit , implicit feelings expressed
in text. The most existing approaches are able to detect either explicit expressions or implicit expressions of
sentiments in the text separately. In this proposed framework it will detect both Implicit and Explicit
expressions available in the meeting transcripts. It will classify the Positive, Negative, Neutral words and
also identify the topic of the particular meeting transcripts by using fuzzy logic. This paper aims to add
some additional features for improving the classification method. The quality of the sentiment classification
is improved using proposed fuzzy logic framework .In this fuzzy logic it includes the features like Fuzzy
rules and Fuzzy C-means algorithm.The quality of the output is evaluated using the parameters such as
precision, recall, f-measure. Here Fuzzy C-means Clustering technique measured in terms of Purity and
Entropy. The data set was validated using 10-fold cross validation method and observed 95% confidence
interval between the accuracy values .Finally, the proposed fuzzy logic method produced more than 85 %
accurate results and error rate is very less compared to existing sentiment classification techniques.
A Review on Sentimental Analysis of Application ReviewsIJMER
As with rapid evolution of computer technology and smart phones mobile applications
become very important part of our life. It is very difficult for customers to keep track of different
applications reviews so sentimental analysis is used. Sentimental analysis is effective and efficient
evolution of customer’s opinion in real time. Sentimental analysis for applications review is performed
two approaches statistical model based approaches and Natural Language Processing (NLP) based
approaches to create rules. Two schemes used for analyzing the textual comments- aspect level
sentimental analysis analyses the text and provide a label on each aspect then scores on multiple
aspects are aggregated and result for reviews shown in graphs. Second scheme is document level
analyses which comprising of adjectives, adverbs and verbs and n-gram feature extraction. I have also
used our SentiWordNet scheme to compute the document-level sentiment for each movie reviewed
and compared the results with results obtained using Alchemy API. The sentiment profile of a movie is
also compared with the document-level sentiment result. The results obtained show that my scheme
produces a more accurate and focused sentiment profile than the simple document-level sentiment
analysis.
Similar to Sentiment Analysis in Marathi Language (20)
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A Review on Real Time Integrated CCTV System Using Face Detection for Vehicle...rahulmonikasharma
We are describes the technique for real time human face detection and counting the number of passengers in vehicle and also gender of the passengers.The Image processing technology is very popular,now at present all are going to use it for various purpose. It can be applied to various applications for detecting and processing the digital images. Face detection is a part of image processing. It is used for finding the face of human in a given area. Face detection is used in many applications such as face recognition, people tracking, or photography. In this paper,The webcam is installed in public vehicle and connected with Raspberry Pi model. We use face detection technique for detecting and counting the number of passengers in public vehicle via webcam with the help of image processing and Raspberry Pi.
Considering Two Sides of One Review Using Stanford NLP Frameworkrahulmonikasharma
Sentiment analysis is a type of natural language processing for tracking the mood of the public about a particular product or a topic and is useful in several ways. Polarity shift is the most classical task which aims at classifying the reviews either positive or negative. But in many cases, in addition to the positive and negative reviews, there still many neutral reviews exist. However, the performance sometimes limited due to the fundamental deficiencies in handling the polarity shift problem. We propose an Improvised Dual Sentiment Analysis (IDSA) model to address this problem for sentiment classification. We first propose a novel data expansion technique by creating sentiment-reversed review for each training and test review. We develop a corpus based method to construct a pseudo-antonym dictionary. It removes DSA’s dependency on an external antonym dictionary for review reversion. We conduct a range of experiments and the results demonstrates the effectiveness of DSA in addressing the polarity shift in sentiment classification. .
A New Detection and Decoding Technique for (2×N_r ) MIMO Communication Systemsrahulmonikasharma
The requirements of fifth generation new radio (5G- NR) access networks are very high capacity and ultra-reliability. In this paper, we proposed a V-BLAST2 × N_r MIMO system that is analyzed, improved, and expected to achieve both very high throughput and ultra- reliability simultaneously.A new detection technique called parallel detection algorithm is proposed. The performance of the proposed algorithm compared with existing linear detection algorithms. It was seen that the proposed technique increases the speed of signal transmission and prevents error propagation which may be present in serial decoding techniques. The new algorithm reduces the bit error probability and increases the capacity simultaneouslywithout using a standard STC technique. However, it was seen that the BER of systems using the proposed algorithm is slightly higher than a similar system using only STC technique. Simulation results show the advantages of using the proposed technique.
Broadcasting Scenario under Different Protocols in MANET: A Surveyrahulmonikasharma
A wireless network enables people to communicate and access applications and information without wires. This provides freedom of movement and the ability to extend applications to different parts of a building, city, or nearly anywhere in the world. Wireless networks allow people to interact with e-mail or browse the Internet from a location that they prefer. Adhoc Networks are self-organizing wireless networks, absent any fixed infrastructure. broadcasting of data through proper channel is essential. Various protocols are designed to avoid the loss of data. In this paper an overview of different broadcast protocols are discussed.
Sybil Attack Analysis and Detection Techniques in MANETrahulmonikasharma
Security is important for many sensor network applications. A particularly harmful attack against sensor and ad hoc networks is known as the Sybil attack [6], where a node Illegitimately claims multiple identities.Mobility cause a main problem when we talk about security in Mobile Ad-hoc networks. It doesn’t depend on fixed architecture, the nodes are continuously moving in a random fashion. In this article we will focus on identifying the Sybil attack in MANET. It uses air medium for communication so it is more prone to the attack. Sybil attack is one in which single node present multiple fake identities to other nodes, which cause destruction.
A Landmark Based Shortest Path Detection by Using A* and Haversine Formularahulmonikasharma
In 1900, less than 20 percent of the world populace lived in cities, in 2007, fair more than 50 percent of the world populace lived in cities. In 2050, it has been anticipated that more than 70 percent of the worldwide population (about 6.4 billion individuals) will be city tenants. There's more weight being set on cities through this increment in population [1]. With approach of keen cities, data and communication technology is progressively transforming the way city regions and city inhabitants organize and work in reaction to urban development. In this paper, we create a nonspecific plot for navigating a route throughout city A asked route is given by utilizing combination of A* Algorithm and Haversine equation. Haversine Equation gives least distance between any two focuses on spherical body by utilizing latitude and longitude. This least distance is at that point given to A* calculation to calculate minimum distance. The method for identifying the shortest path is specify in this paper.
Processing Over Encrypted Query Data In Internet of Things (IoTs) : CryptDBs,...rahulmonikasharma
Internet of Things (IoT) is the developing technologies that would be the biggest agents to modify the current world. Machine-to-machine communications perform with virtual, mobile and instantaneous connections. In IoT system, it consists of data-gathering sensors various other household devices. Intended for protecting IoT system, the end-to-end secure communication is a necessary measure to protect against unauthorized entities (e.g., modification attacks and eavesdropping,) and the data unprotected on the Cloud. The most important concern hereby is how to preserve the insightful information and to provide the privacy of user data. In IoT, the encrypted data computing is based on techniques appear to be promising approaches. In this paper, we discuss about the recent secure database systems, which are capable to execute SQL queries over encrypted data.
Quality Determination and Grading of Tomatoes using Raspberry Pirahulmonikasharma
In India cultivation of tomatoes is carried out by traditional methods and techniques. Today tremendous improvement in field of agriculture technologies and products can be seen. The tomatoes affect the overall production drastically. Image processing technique can be key technique for finding good qualities of tomatoes and grading. This work aimed to study different types of algorithms used for quality grading and sorting of fruit from the acquire image. In previous years several types of techniques are applied to analyses the good quality fruits. A simple system can be implemented using Raspberry pi with computer vision technology and image processing algorithms.
Comparative of Delay Tolerant Network Routings and Scheduling using Max-Weigh...rahulmonikasharma
Network management and Routing is supportively done by performing with the nodes, due to infrastructure-less nature of the network in Ad hoc networks or MANET. The nodes are maintained itself from the functioning of the network, for that reason the MANET security challenges several defects. Routing process and Scheduling is a significant idea to enhance the security in MANET. Other than, scheduling has been recognized to be a key issue for implementing throughput/capacity optimization in Ad hoc networks. Designed underneath conventional (LT) light tailed assumptions, traffic fundamentally faces Heavy-tailed (HT) assumption of the validity of scheduling algorithms. Scheduling policies are utilized for communication networks such as Max-Weight, backpressure and ACO, which are provably throughput optimality and the Pareto frontier of the feasible throughput region under maximal throughput vector. In wireless ad-hoc network, the issue of routing and optimal scheduling performs with time varying channel reliability and multiple traffic streams. Depending upon the security issues within MANETs in this paper presents a comparative analysis of existing scheduling policies based on their performance to progress the delay performance in most scenarios. The security issues of MANETs considered from this paper presents a relative analysis of existing scheduling policies depend on their performance to progress the delay performance in most developments.
DC Conductivity Study of Cadmium Sulfide Nanoparticlesrahulmonikasharma
The dc conductivity of consolidated nanoparticle of CdS has been studied over the temperature range from 303 K to 523 K and the conductivity has been found to be much larger than that of single crystals.
A Survey on Peak to Average Power Ratio Reduction Methods for LTE-OFDMrahulmonikasharma
OFDM (Orthogonal Frequency Division Multiplexing) is generally preferred for high data rate transmission in digital communication. The Long-Term Evolution (LTE) standards for the fourth generation (4G) wireless communication systems. Orthogonal Frequency Division Multiple Access (OFDMA) and Single Carrier Frequency Division Multiple Access (SC-FDMA) are the two multiple access techniques which are generally used in LTE.OFDM system has a major shortcoming of high peak to average power ratio (PAPR) value. This paper explains different PAPR reduction techniques and presents a comparison of the various techniques based on theoretical results. It also presents a survey of the various PAPR reduction techniques and the state of the art in this area.
IOT Based Home Appliance Control System, Location Tracking and Energy Monitoringrahulmonikasharma
Home automation has been a dream of sciences for so many years. It could wind up conceivable in twentieth century simply after power all family units and web administrations were begun being utilized on across the board level. The point of home robotization is to give enhanced accommodation, comfort, vitality effectiveness and security. Vitality checking and protection holds prime significance in this day and age in view of the irregularity between control age and request observing frameworks accessible in the market. Ordinarily, customers are disappointed with the power charge as it doesn't demonstrate the power devoured at the gadget level. This paper shows the outline and execution of a vitality meter utilizing Arduino microcontroller which can be utilized to gauge the power devoured by any individual electrical apparatus. The primary expectation of the proposed vitality meter is to screen the power utilization at the gadget level, transfer it to the server and build up remote control of any apparatus. So we can screen the power utilization remotely and close down gadgets if vital. The car segment is additionally one of the application spaces where vehicle can be made keen by utilizing "IOT". So a vehicle following framework is additionally executed to screen development of vehicles remotely.
Thermal Radiation and Viscous Dissipation Effects on an Oscillatory Heat and ...rahulmonikasharma
An anticipated outcome that is intended chapter is to investigate effects of magnetic field on an oscillatory flow of a viscoelastic fluid with thermal radiation, viscous dissipation with Ohmic heating which bounded by a vertical plane surface, have been studied. Analytical solutions for the quasi – linear hyperbolic partial differential equations are obtained by perturbation technique. Solutions for velocity and temperature distributions are discussed for various values of physical parameters involving in the problem. The effects of cooling and heating of a viscoelastic fluid compared to the Newtonian fluid have been discussed.
Advance Approach towards Key Feature Extraction Using Designed Filters on Dif...rahulmonikasharma
In fast growing database repository system, image as data is one of the important concern despite text or numeric. Still we can’t replace test on any cost but for advancement, information may be managed with images. Therefore image processing is a wide area for the researcher. Many stages of processing of image provide researchers with new ideas to keep information safe with better way. Feature extraction, segmentation, recognition are the key areas of the image processing which helps to enhance the quality of working with images. Paper presents the comparison between image formats like .jpg, .png, .bmp, .gif. This paper is focused on the feature extraction and segmentation stages with background removal process. There are two filters, one is integer filter and second one is floating point Filter, which is used for the key feature extraction from image. These filters applied on the different images of different formats and visually compare the results.
Alamouti-STBC based Channel Estimation Technique over MIMO OFDM Systemrahulmonikasharma
The examination on various looks into on MIMO STBC framework in order to accomplish the higher framework execution is standard that the execution of the remote correspondence frameworks can be improved by usage numerous transmit and get radio wires, that is normally gathered on the grounds that the MIMO procedure, and has been incorporated. The Alamouti STBC might be a promising because of notice the pick up inside the remote interchanges framework misuse MIMO. To broaden the code rate and furthermore the yield of the symmetrical zone time square code for more than 4 transmit reception apparatuses is examined. The outlined framework is beated once forced with M-PSK (i.e upto 32-PSK) regulation. The channel estimation examine in these conditions.
Empirical Mode Decomposition Based Signal Analysis of Gear Fault Diagnosisrahulmonikasharma
A vibration investigation is about the specialty of searching for changes in the vibration example, and after that relating those progressions back to the machines mechanical outline. The level of vibration and the example of the vibration reveal to us something about the interior state of the turning segment. The vibration example can let us know whether the machine is out of adjust or twisted. Al-so blames with the moving components and coupling issues can be distinguished. This paper shows an approach for equip blame investigation utilizing signal handling plans. The information has been taken from college of ohio, joined states. The investigation has done utilizing MATLAB software.
This paper discusses a new algorithm of a univariate method, which is vitally important to develop a short-term load forecasting module for planning and operation of distribution system. It has many applications including purchasing of energy, generation and infrastructure development etc. We have discussed different time series forecasting approaches in this paper. But ARIMA has proved itself as the most appropriate method in forecasting of the load profile for West Bengal using the historical data of the year of 2017. Auto Regressive Integrated Moving Average model gives more accuracy level of load forecast than any other techniques. Mean Absolute Percentage Error (MAPE) has been calculated for the mentioned forecasted model.
Impact of Coupling Coefficient on Coupled Line Couplerrahulmonikasharma
The coupled line coupler is a type of directional coupler which finds practical utility. It is mainly used for sampling the microwave power. In this paper, 3 couplers A,B & C are designed with different values of coupling coefficient 6dB,10dB & 18dB respectively at a frequency of 2.5GHz using ADS tool. The return loss, isolation loss & transmission loss are determined. The design & simulation is done using microstrip line technology.
Design Evaluation and Temperature Rise Test of Flameproof Induction Motorrahulmonikasharma
The ignition of flammable gases, vapours or dust in presence of oxygen contained in the surrounding atmosphere may lead to explosion. Flameproof three phase induction motors are the most common and frequently used in the process industries such as oil refineries, oil rigs, petrochemicals, fertilizers, etc. The design of flameproof motor is such that it allows and sustain explosion within the enclosure caused by ignition of hazardous gases without transmitting it to the external flammable atmosphere. The enclosure is mechanically strong enough to withstand the explosion pressure developed inside it. To prevent an explosion due to hot spot on the surface of the motor, flameproof induction motors are subjected to heat run test to determine the maximum surface temperature and temperature class with respect to the ignition temperature of the surrounding flammable gas atmosphere. This paper highlights the design features of flameproof motors and their surface temperature classification for different sizes.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
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Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
1. International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
Volume: 5 Issue: 8 21 – 25
_______________________________________________________________________________________________
21
IJRITCC | August 2017, Available @ http://www.ijritcc.org
_______________________________________________________________________________________
Sentiment Analysis in Marathi Language
1
Snehal V. Pawar, 2
Prof. Swati Mali
Dept. Of Computer Technology
K. J. Somaiya College Of Engineering
VIDYAVIHAR, MUMBAI
1
snehal.vp@somaiya.edu, 2
swatimali@somiaya.edu
Abstract— Sentiment analysis is inevitable in current era. Internet is growing day-by-day. Now-a-days everything is online. We can shop, buy,
and sell online. People can give feedbacks / opinions on the internet. Customers can compare among various products by analyzing the product
reviews. As more and more people from different age groups and languages are becoming new internet users, we need it in regional languages.
Till date most of the work related to sentiment analysis has been done in English language. But when it comes to Indian languages, not much
research has done except for few languages. This paper mainly focuses on performing sentiment analysis in one of the Indian languages i.e.
Marathi.
Keywords- sentiment analysis, SVM, NB,Max.Entropy
__________________________________________________*****_________________________________________________
I. INTRODUCTION
Sentiment analysis is an ongoing research field. In
Sentiment analysis based on the sentiment value it is decided
whether the sentence is positive, negative or neutral. This
helps a lot when you need to rely on people‟s opinion. For
example, if a mobile company launches a new mobile phone,
it needs to know whether the customers like the product or not.
They need to know that their product has fulfilled the
customer‟s requirements or it needs more improvements. The
easier way to understand that is to focus on the reviews /
feedbacks. But reading all the feedbacks /reviews is itself a
difficult task and concluding something from them adds up to
the pile. If there is some technique or algorithm which
analyses all the reviews and tell you whether a review is
positive or negative, it will save a lot of time and overhead.
Also if the algorithm tells you that how much positive or
negative reviews you received for a particular product or for
which aspect it got positive reviews and which aspects need
improvements then it will become easier for the company or
manufacturer to understand the customer‟s need and that‟s
where Sentiment analysis come into picture.
Sentiment analysis techniques are broadly
categorized into two approaches; machine learning and lexicon
based approach. In machine learning approach, machine
learning algorithms are used while in lexicon approach
depends on the lexicon which consists of pre-defined
sentiment words. Lexicon based approach is further divided
into corpus-based and dictionary based approach.
If there is an algorithm which extract all the reviews
related to a product and analyze them and tell you whether the
product is good or bad or the algorithm will analyze the
reviews of a movie and can tell you whether it is a hit or flop,
then it will reduce a lot of overhead.
That is where sentiment analysis comes into
existence. It uses various techniques to analyze the given data
and extract sentiments out of it. The first step in sentiment
analysis is to gather the data. The second step is to clean and
pre-process the data. Then the data is given to the sentiment
analysis techniques for further processing. At the end of the
process, it assigns polarity to the data based on which it is
determined that the data is either positive or negative.
As internet is growing day by day and people are
expressing their opinions in various languages, we need to find
an approach to extract sentiments out of them. Sentiment
analysis is very important to understand the people opinions,
but English isn't everyone's forte. Some people do want to
write/express opinion in their mother tongue. To perform
Sentiment analysis on this data, we do not have much resource
for Marathi language available, as most of the work of
Sentiment analysis is done in English language. Therefore this
is a basic approach to perform sentiment analysis on data in
Marathi language.
To perform sentiment analysis in Marathi language,
we are using lexicon based techniques which requires lexicon
containing positive words and negative words along with their
polarity. Later they will be used to analyze the sentiment of
the sentence. There will be a training set to train the classifier
and “test data” to evaluate the performance.
The paper consists of the process of Sentiment
analysis. Section II describes the previous work done by other
authors along with their techniques and results. The motive
behind the implementation of this approach is given in Section
III. Section IV explains the proposed system, techniques used
2. International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
Volume: 5 Issue: 8 21 – 25
_______________________________________________________________________________________________
22
IJRITCC | August 2017, Available @ http://www.ijritcc.org
_______________________________________________________________________________________
in proposed system and issues related to sentiment analysis.
The architecture is explained in section V with results of
proposed system.
II. PREVIOUS WORK
Business holders want to know the requirements of the
customers, also the opinions about the product. Customer
feedback is there from a long time. Today in technology era,
this feedback is emerged as sentiment analysis. Sentiment
analysis started in late 2000s, but it is been in effect since 2004
in product reviews area. There are a lot of people who have
done research on sentiment analysis, its process and its various
techniques. There are some authors who have worked on the
languages other than English. The ones who have performed
Sentiment analysis in Indian languages, few of them are listed
below.
The [1] is about movie review data in Hindi. It performs
opinion mining at document level. It classifies documents in
three categories viz., positive, negative and neutral. It has used
Machine learning approach and Pos tagging. In the POS
tagging only adjectives are concerned. Authors have
performed both the methods in Machine Learning i.e.
supervised and unsupervised. They have taken care of the
negation as well. They have achieved 87.1% accuracy.
In [2], authors have done sentiment analysis on mixed
language sentences. Here they have considered only two
languages i.e. Hindi and English. The analysis has been done
in phrase as well as sub-phrase level of the sentence.
Grammatical transitions are taken into consideration while
predicting the overall sentiment of the sentence. They have
able to achieve accuracy up to 91%.
[3]This is mainly a survey paper. It gives various methods
used in opinion mining. It is the summary of what work has
been done related to opinion mining in Hindi language. It
describes different challenges that need to be overcome while
performing opinion mining in Hindi language. Authors have
accepted that it is not easy to perform sentiment analysis in
Hindi as it is a natural language and lack of resources.
There is a case study written on sentiment analysis using
mobile phone reviews in Kannada language [4]. To gather the
product reviews lexicon based approach has used. To
determine the polarity naive Bayes classifier has applied.
There is very less amount of work done in Kannada sentiment
analysis. In this paper, they have used aspect based sentiment
analysis. They have managed to get approx. 65% accuracy
with their proposed model.
[5]In this paper sentiment analysis is done on movie reviews
in Malayalam language. They have used rule based approach
for sentiment analysis. Negation handling has done in order to
extract sentiment from the review. The corpus is made from
Malayalam websites. They have got 85% accuracy.
In the second paper [6] by the same authors as [5], they have
taken the research work further ahead. They have used
machine learning with rule based approach which gave them
91% accuracy by keeping the same corpus. They have used
two techniques Support vector machine (SVM) and
Conditional random fields (CRF). Authors have concluded
that SVM is better than CRF.
In [7], authors have analyzed Bengali language for sentiment
analysis. They have used SentiWordNet and WordNet to build
the corpus. First it finds part of speech and then on the basis of
the adjective they assign polarity to it. They have come up
with their own method for sentiment extraction. They have
achieved up to 90% accuracy in their results.
Another paper [8] has performed sentiment analysis in
Bengali language using the horoscope in the newspaper.
Approx. 6000 sentences have analyzed. They have used various
machine learning techniques along with unigram and bigram
methods. They have experimented SVM with unigram features
without removing stop words which gave them 98.7%
accuracy.
III. MOTIVATION
Marathi is an Indian language. It is the official language of
Maharashtra. There were 73 million speakers in 2007; Marathi
ranks 19th in the list of most spoken languages in the world.
Marathi has the fourth largest number of native speakers in
India, after Hindi, Bengali and Telagu in that order. Marathi
employs agglutinative and analytical forms. Marathi uses
many morphological processes to join words together,
forming compounds. Now-a-days various Marathi typing
software are widely used and display interface packages are
now available on Windows and Linux. Many Marathi
websites, including Marathi newspapers, have become
popular. People sometimes use regional language to express
their opinions on internet, Marathi is one of them. To perform
Sentiment analysis on this data, we do not have much resource
available, since not much work has been done on this topic.
Most of the work of Sentiment analysis is done in English
language. Therefore this is a basic approach to perform
sentiment analysis on data in Marathi language.
IV. PROPOSED SYSTEM
There are various techniques for Sentiment analysis, broadly
categorized into two approaches; machine learning and lexicon
based approach. In machine learning approach machine
learning algorithms are used while lexicon approach depends
on the lexicon which consists of pre-defined sentiment words.
In this project, lexicon based approach is used which
requires a lexicon consisting positive and negative words. A
dataset is created comprise of positive and negative words
consisting 100 positive and 100 negative words. Positive words
are having polarity 1 and negative words are having polarity 0.
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A. Support Vector Machine
Support Vector Machine is a supervised machine learning
algorithm for classification or regression problems where the
dataset teaches SVM about the classes so that SVM can
classify any new data. It works by classifying the data into
different classes by finding a line which separates the training
data set into classes. In this algorithm, we plot each data item
as a point in n-dimensional space with the value of each feature
being the value of a particular coordinate. Then, we perform
classification by finding the hyper-plane that differentiates the
two classes very well. SVM offers best classification
performance on the training data. SVM renders more efficiency
for correct classification of the future data. The best thing about
SVM is that it does not make any strong assumptions on data.
It does not over-fit the data. It is effective in high dimensional
spaces. It is memory efficient. Though, it doesn‟t perform well,
when we have large data set because the required training time
is higher. There are several applications such as Classification
of images, Hand-written characters recognition, The SVM
algorithm has been widely applied in the biological and other
sciences. SVM is commonly used for stock market forecasting
by various financial institutions. For instance, it can be used to
compare the relative performance of the stocks when compared
to performance of other stocks in the same sector. The relative
comparison of stocks helps manage investment making
decisions based on the classifications made by the SVM
learning algorithm.
B. Naïve Bayes
A classifier is a function that allocates a population‟s element
value from one of the available categories. For instance, Spam
Filtering is a popular application of Naïve Bayes algorithm.
Spam filter here, is a classifier that assigns a label “Spam” or
“Not Spam” to all the emails. Naïve Bayes Classifier is
amongst the most popular learning method grouped by
similarities that works on the popular Bayes Theorem of
Probability- to build machine learning models particularly for
disease prediction and document classification. It is a
classification technique based on Bayes theorem. Naive Bayes
classifier assumes that a particular feature is independent.
Naive Bayes model is easy to build and particularly useful for
very large data sets. Naive Bayes is known to outperform many
classification methods.
Figure 1. Naïve Bayes probabalistic model.
Naïve bayes is easy and fast as it needs less training data. It
can be used for making predictions in real time. This algorithm
is also well known for multi class prediction feature. It can be
used for Text classification, Spam Filtering, Sentiment
Analysis. Limitation of Naive Bayes is the assumption of
independent feature. In real life, it is almost impossible to get
independent features.
Applications include Spam filtering, Classify documents based
on topics, Sentiment analysis, Information retrieval, Image
classifications, Medical field, Document Categorization. Naïve
Bayes Algorithm is also used for classifying news articles
about Technology, Entertainment, Sports, Politics, etc.
C. Maximum Entropy
The Max Entropy classifier is a probabilistic classifier. Max
Entropy does not assume that the features are independent of
each other. The classifier is based on the principle of Maximum
Entropy from all the models that fit the training data, selects the
one which has the largest entropy. The principle of maximum
entropy states that, subject to precisely stated prior data,
the probability distribution which best represents the current
state of knowledge is the one with largest entropy. The Max
Entropy classifier can be used to solve a large variety of text
classification problems such as language detection, topic
classification, sentiment analysis and more. Due to the
minimum assumptions that the Maximum Entropy classifier
makes, we regularly use it when it is unsafe to make any such
assumptions. The Max Entropy requires more time to train
comparing to Naive Bayes.
D. Issues related to Sentiment Analysis
There are some issues related to sentiment analysis as follows:
1. Named entity recognition: - Named-entity
recognition is a subtask of information
extraction that seeks to locate and classify named
entities in text into pre-defined categories such as the
names of persons, organizations, locations,
expressions of times, quantities, monetary values,
percentages, etc. The problem is we do not know
what a person actually wants to say. For example
“Bank of America” is one name which has “America”
as substring which may be considered as noun while
tagging.
2. Sarcasm: - In sentiment analysis sarcasm plays an
important role. It may have positive words or
negative words but the meaning of the sentence is not
as it seems to be. Detection of sarcasm is important in
sentiment analysis to get the exact meaning of the
sentence but it is a serious technical challenge.
3. Anaphora resolution: - The problem is to
understand what a noun or pronoun refers to such as
“we watched the movie and went to dinner, it was
awful”. What does “awful” refer to?
4. International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
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4. Polarity: - In general the polarity of particular word
or sentence is positive or negative or neutral. But how
much positive or negative is another question.
“Good” and “Best” both are positive but second one
is a stronger sentiment than the first one.
5. Use of abbreviations poor spelling punctuation
grammar: - Due to these issues it is difficult to
identify the sentiment or aspect on which opinion is
expressed.
6. Sentiment lexicon acquisition: - There are a lot of
words available in the dictionary for English
language. But opinions can be expressed in the form
of words, emoticons, slang words etc. having all these
words in the lexicon is not that easy. Also multi-
lingual words can be there. Therefore finding
sentiment in such opinions is a difficult task.
7. Negation handling: - Only writing not in the
sentence does not make it a negative sentence such as
“The food is not bad” has positive opinion but it may
consider as negative because of the “not” word.
8. Aspect based Sentiment Analysis: - We should
know on which aspect the opinion is expressed so as
to evaluate the sentiment. Rather than evaluating
sentiment of whole sentence finding the aspect is
more important.
There are other overheads also such as:
1. On internet there is a lot of spam and fake messages.
We need to eliminate the fake reviews to get efficient
sentiment analysis.
2. There are sentiment analysis tools available but they
are expensive which cannot affordable by common
person.
3. The sentiments are domain dependent. Therefore
features which give good performance in one domain
may fail in other domain.
V. ARCHITECTURE
Figure 2. Architecture of proposed system.
Steps involved in proposed system-
Step 1: A sentence is given as an input.
Step 2: Each word in the given sentence is extracted
Step 3: The extracted word is searched in the dataset
Step 4: If found its polarity is collected
Step 5: If polarity is 1 then sentence is positive
Step 6: If polarity is 0 then sentence is negative
As given in the architecture diagram, a sentence is analyzed
based on the sentiment words it contains regardless of other
words. For this purpose, only adjectives are considered. If the
sentiment word is found in our positive dataset, then the
sentence is considered as positive. If the sentiment word is
found in our negative dataset, then the sentence is considered
as negative. If not found in any then it is considered as neutral.
.
A. Results
A user interactive webpage is created which will ask user to
enter a sentence. Results are shown in three tables‟ viz.,
positive words, negative words, neutral words. Those words
matched with positive words of the dataset are considered as
positive and those words matched with negative words of the
dataset are considered as negative. Words not matching with
either of positive words and negative words are considered as
neutral.
TABLE I. EXAMPLES
Sentences
Polarities
Positive Negative Neutral
आमचे शेजारी
भाांडखोर आहेत
भाांडखोर
आमचे, शेजारी
,आहेत
आकाश हा कऩटी
माणूस आहे
कऩटी
आकाश, हा, माणूस,
आहे
अजजुन धनजर्वुद्येत
कज शऱ होता
कज शऱ
अजजुन, धनजर्वुद्येत,
होता
आकाश प्रामाणणक
मजऱगा आहे
प्रामाणणक
आकाश, मजऱगा,
आहे
काश्ममर हे एक
रमणीय ठिकाण
आहे
काश्ममर, हे, एक,
रमणीय, ठिकाण,
आहे
ही कादांबरी नीरस
आहे
ही, कादांबरी, नीरस,
आहे
As per above examples, the words „भाांडखोर‟, „कऩटी‟ are
having polarity „0‟ which indicates that they are present in
„negative_words‟ list, therefore considered as negative words
and the sentences comprising such words are referred as
negative.
Similarly „कज शऱ‟, „प्रामाणणक‟ both are having polarity „1‟
which indicates that they are present in „positive_words‟ list,
5. International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
Volume: 5 Issue: 8 21 – 25
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therefore considered as positive words and the sentences
comprising such words are referred as positive.
The word „रमणीय‟ in „काश्ममर हे एक रमणीय ठिकाण आहे‟
is positive, but it is not present in our „positive_words‟ list
therefore it is considered as neutral.
Similarly, the word „नीरस‟ in „ही कादांबरी नीरस आहे‟ is
negative, but it is not present in our „negative_words‟ list
therefore it is considered as neutral.
VI. CONCLUSION AND FUTURE WORK
Different research papers are studied to understand how
different techniques work and how they affect sentiment
analysis under different circumstances. Based on the research
done during the proposed work following conclusions are
made -
The project requires analyzing data in Marathi
language.
It is slightly difficult to process data in Marathi as it
is a natural language and not much work has been
done related to this topic.
According to the results, the words which are not in
the database are considered as neutral though they are
sentiment words. Therefore the database should be as
rich as possible for efficient results.
This concludes that not only the techniques but the resources
are also more important for better results.
The dataset will be enhanced as part of future work. Also other
algorithms and techniques will be implemented to increase the
efficiency.
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