NLP (Natural Language Processing) is a mechanism that helps computers to know natural languages like English. In general, computers can understand data, tables etc. which are well formed. But when it involves natural languages, it's unacceptable for computers to spot them. NLP helps to translate the tongue in such a fashion which will be easily processed by modern computers. Financial Tracker is an approach which will use NLP as a tool and can differentiate the user messages in various categories. the appliance of the approach will be seen at multiple levels. At a personal level, this permits users to filtrate useful financial messages from an large junk of text messages. On the opposite hand, from an industrial point of view, this can be useful in services like online loan disbursal, which are hitting the market nowadays. These services attempt to provide online loans to individuals in an exceedingly faster and quicker manner. But when it involves business view, loan recovery from customers becomes a really important & crucial aspect. As most such services can’t take strict legal actions against the fraud customers, it becomes a requirement that loan should be provided only to those customers who deserve it. At that time, this model can come under the image. As a business we will find the user’s messages from their inbox (after taking permission from the users). These messages are often filtered using NLP which might help to differentiate various types of messages within the user's inbox which might further be used as a content for further prediction and analysis on user’s behaviour in terms of cash related transactions.
2. an efficient approach for web query preprocessing edit satIAESIJEECS
The emergence of the Web technology generated a massive amount of raw data by enabling Internet users to post their opinions, comments, and reviews on the web. To extract useful information from this raw data can be a very challenging task. Search engines play a critical role in these circumstances. User queries are becoming main issues for the search engines. Therefore a preprocessing operation is essential. In this paper, we present a framework for natural language preprocessing for efficient data retrieval and some of the required processing for effective retrieval such as elongated word handling, stop word removal, stemming, etc. This manuscript starts by building a manually annotated dataset and then takes the reader through the detailed steps of process. Experiments are conducted for special stages of this process to examine the accuracy of the system.
AUTOMATED SQL QUERY GENERATOR BY UNDERSTANDING A NATURAL LANGUAGE STATEMENTijnlc
This project aims to develop a system which converts a natural language statement into MySQL query to retrieve information from respective database. The system mainly focuses on creation of complex queries which includes nested queries with more than two-level depth, queries with aggregate functions, having clause, group by clause and co-related queries which are formed due to constraint on aggregate function. The natural language input statement taken from the user is passed through various OpenNLP natural language processing techniques like Tokenization, Parts of Speech Tagging, Stemming and Lemmatization to get the statement in the desired form. The statement is further processed to extract the type of query, the basic clause, which specifies the required entities from the database and the condition clause, which specifies constraints on the basic clause. The final query is generated by converting the basic and condition clauses to their query form and then concatenating the condition query to the basic query. Currently, the system works only with MySQL database.
Enhanced Retrieval of Web Pages using Improved Page Rank Algorithmijnlc
Information Retrieval (IR) is a very important and vast area. While searching for context web returns all
the results related to the query. Identifying the relevant result is most tedious task for a user. Word Sense
Disambiguation (WSD) is the process of identifying the senses of word in textual context, when word has
multiple meanings. We have used the approaches of WSD. This paper presents a Proposed Dynamic Page
Rank algorithm that is improved version of Page Rank Algorithm. The Proposed Dynamic Page Rank
algorithm gives much better results than existing Google’s Page Rank algorithm. To prove this we have
calculated Reciprocal Rank for both the algorithms and presented comparative results.
TALASH: A SEMANTIC AND CONTEXT BASED OPTIMIZED HINDI SEARCH ENGINEIJCSEIT Journal
The traditional search engine have shortcoming that they retrieve irrelevant information. Query expansion
with relevant words increases the performance of search engines, but finding and using the relevant words
is an open problem. This paper presents a Hindi search engine in which we describe three models for
query enhancement. They are based on lexical variance, user context and combination of both techniques.
TEXT SENTIMENTS FOR FORUMS HOTSPOT DETECTIONijistjournal
The user generated content on the web grows rapidly in this emergent information age. The evolutionary changes in technology make use of such information to capture only the user’s essence and finally the useful information are exposed to information seekers. Most of the existing research on text information processing, focuses in the factual domain rather than the opinion domain. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyses the forum text data and computes value for each word of text. The proposed approach combines K-means clustering and Support Vector Machine with PSO (SVM-PSO) classification algorithm that can be used to group the forums into two clusters forming hotspot forums and non-hotspot forums within the current time span. The proposed system accuracy is compared with the other classification algorithms such as Naïve Bayes, Decision tree and SVM. The experiment helps to identify that K-means and SVM-PSO together achieve highly consistent results.
2. an efficient approach for web query preprocessing edit satIAESIJEECS
The emergence of the Web technology generated a massive amount of raw data by enabling Internet users to post their opinions, comments, and reviews on the web. To extract useful information from this raw data can be a very challenging task. Search engines play a critical role in these circumstances. User queries are becoming main issues for the search engines. Therefore a preprocessing operation is essential. In this paper, we present a framework for natural language preprocessing for efficient data retrieval and some of the required processing for effective retrieval such as elongated word handling, stop word removal, stemming, etc. This manuscript starts by building a manually annotated dataset and then takes the reader through the detailed steps of process. Experiments are conducted for special stages of this process to examine the accuracy of the system.
AUTOMATED SQL QUERY GENERATOR BY UNDERSTANDING A NATURAL LANGUAGE STATEMENTijnlc
This project aims to develop a system which converts a natural language statement into MySQL query to retrieve information from respective database. The system mainly focuses on creation of complex queries which includes nested queries with more than two-level depth, queries with aggregate functions, having clause, group by clause and co-related queries which are formed due to constraint on aggregate function. The natural language input statement taken from the user is passed through various OpenNLP natural language processing techniques like Tokenization, Parts of Speech Tagging, Stemming and Lemmatization to get the statement in the desired form. The statement is further processed to extract the type of query, the basic clause, which specifies the required entities from the database and the condition clause, which specifies constraints on the basic clause. The final query is generated by converting the basic and condition clauses to their query form and then concatenating the condition query to the basic query. Currently, the system works only with MySQL database.
Enhanced Retrieval of Web Pages using Improved Page Rank Algorithmijnlc
Information Retrieval (IR) is a very important and vast area. While searching for context web returns all
the results related to the query. Identifying the relevant result is most tedious task for a user. Word Sense
Disambiguation (WSD) is the process of identifying the senses of word in textual context, when word has
multiple meanings. We have used the approaches of WSD. This paper presents a Proposed Dynamic Page
Rank algorithm that is improved version of Page Rank Algorithm. The Proposed Dynamic Page Rank
algorithm gives much better results than existing Google’s Page Rank algorithm. To prove this we have
calculated Reciprocal Rank for both the algorithms and presented comparative results.
TALASH: A SEMANTIC AND CONTEXT BASED OPTIMIZED HINDI SEARCH ENGINEIJCSEIT Journal
The traditional search engine have shortcoming that they retrieve irrelevant information. Query expansion
with relevant words increases the performance of search engines, but finding and using the relevant words
is an open problem. This paper presents a Hindi search engine in which we describe three models for
query enhancement. They are based on lexical variance, user context and combination of both techniques.
TEXT SENTIMENTS FOR FORUMS HOTSPOT DETECTIONijistjournal
The user generated content on the web grows rapidly in this emergent information age. The evolutionary changes in technology make use of such information to capture only the user’s essence and finally the useful information are exposed to information seekers. Most of the existing research on text information processing, focuses in the factual domain rather than the opinion domain. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyses the forum text data and computes value for each word of text. The proposed approach combines K-means clustering and Support Vector Machine with PSO (SVM-PSO) classification algorithm that can be used to group the forums into two clusters forming hotspot forums and non-hotspot forums within the current time span. The proposed system accuracy is compared with the other classification algorithms such as Naïve Bayes, Decision tree and SVM. The experiment helps to identify that K-means and SVM-PSO together achieve highly consistent results.
Modeling the Adaption Rule in Contextaware Systemsijasuc
Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing
systems. Each context-aware application has its own set of behaviors to react to context modifications. This
paper is concerned with the context modeling and the development methodology for context-aware systems.
We proposed a rule-based approach and use the adaption tree to model the adaption rule of context-aware
systems. We illustrate this idea in an arithmetic game application.
Semantic Based Model for Text Document Clustering with IdiomsWaqas Tariq
Text document clustering has become an increasingly important problem in recent years because of the tremendous amount of unstructured data which is available in various forms in online forums such as the web, social networks, and other information networks. Clustering is a very powerful data mining technique to organize the large amount of information on the web. Traditionally, document clustering methods do not consider the semantic structure of the document. This paper addresses the task of developing an effective and efficient method to improve the semantic structure of the text documents. A method has been developed that performs the following: tag the documents for parsing, replacement of idioms with their original meaning, semantic weights calculation for document words and apply semantic grammar. The similarity measure is obtained between the documents and then the documents are clustered using Hierarchical clustering algorithm. The method adopted in this work is evaluated on different data sets with standard performance measures and the effectiveness of the method to develop in meaningful clusters has been proved.
Feature selection, optimization and clustering strategies of text documentsIJECEIAES
Clustering is one of the most researched areas of data mining applications in the contemporary literature. The need for efficient clustering is observed across wide sectors including consumer segmentation, categorization, shared filtering, document management, and indexing. The research of clustering task is to be performed prior to its adaptation in the text environment. Conventional approaches typically emphasized on the quantitative information where the selected features are numbers. Efforts also have been put forward for achieving efficient clustering in the context of categorical information where the selected features can assume nominal values. This manuscript presents an in-depth analysis of challenges of clustering in the text environment. Further, this paper also details prominent models proposed for clustering along with the pros and cons of each model. In addition, it also focuses on various latest developments in the clustering task in the social network and associated environments.
MODIFIED PAGE RANK ALGORITHM TO SOLVE AMBIGUITY OF POLYSEMOUS WORDSIJCI JOURNAL
Ambiguity in natural language has an effect on Information Retrieval (IR) system in general and web
search system in particular. Word sense ambiguity is the reason behind the poor performance of IR system.
If the ambiguous words are correctly disambiguated then IR performance can increase. WSD is defined as
the task of identifying the sense of word in textual context. Word Sense Disambiguation (WSD) is the
central problem of language processing. WSD improves the IR in many ways. Current IR system do not use
explicit WSD and rely on user typing enough content in the query to only retrieve documents relevant to the
intended senses. This paper proposes an algorithm for efficient retrieval of information on the Web
according to user’s need. Results are more accurate and they are according to user’s preference.
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.
Design of optimal search engine using text summarization through artificial i...TELKOMNIKA JOURNAL
Natural language processing is the trending topic in the latest research areas, which allows the developers to create the human-computer interactions to come into existence. The natural language processing is an integration of artificial intelligence, computer science and computer linguistics. The research towards natural Language Processing is focused on creating innovations towards creating the devices or machines which operates basing on the single command of a human. It allows various Bot creations to innovate the instructions from the mobile devices to control the physical devices by allowing the speech-tagging. In our paper, we design a search engine which not only displays the data according to user query but also performs the detailed display of the content or topic user is interested for using the summarization concept. We find the designed search engine is having optimal response time for the user queries by analyzing with number of transactions as inputs. Also, the result findings in the performance analysis show that the text summarization method has been an efficient way for improving the response time in the search engine optimizations.
Improving Sentiment Analysis of Short Informal Indonesian Product Reviews usi...TELKOMNIKA JOURNAL
Sentiment analysis in short informal texts like product reviews is more challenging. Short texts are
sparse, noisy, and lack of context information. Traditional text classification methods may not be suitable
for analyzing sentiment of short texts given all those difficulties. A common approach to overcome these
problems is to enrich the original texts with additional semantics to make it appear like a large document of
text. Then, traditional classification methods can be applied to it. In this study, we developed an automatic
sentiment analysis system of short informal Indonesian texts using Naïve Bayes and Synonym Based
Feature Expansion. The system consists of three main stages, preprocessing and normalization, features
expansion and classification. After preprocessing and normalization, we utilize Kateglo to find some
synonyms of every words in original texts and append them. Finally, the text is classified using Naïve
Bayes. The experiment shows that the proposed method can improve the performance of sentiment
analysis of short informal Indonesian product reviews. The best sentiment classification performance using
proposed feature expansion is obtained by accuracy of 98%.The experiment also show that feature
expansion will give higher improvement in small number of training data than in the large number of them.
Business intelligence analytics using sentiment analysis-a surveyIJECEIAES
Sentiment analysis (SA) is the study and analysis of sentiments, appraisals and impressions by people about entities, person, happening, topics and services. SA uses text analysis techniques and natural language processing methods to locate and extract information from big data. As most of the people are networked themselves through social websites, they use to express their sentiments through these websites.These sentiments are proved fruitful to an individual, business, government for making decisions. The impressions posted on different available sources are being used by organization to know the market mood about the services they are providing. Analyzing huge moods expressed with different features, style have raised challenge for users. This paper focuses on understanding the fundamentals of sentiment analysis, the techniques used for sentiment extraction and analysis. These techniques are then compared for accuracy, advantages and limitations. Based on the accuracy for expexted approach, we may use the suitable technique.
HIGH SPEED DATA RETRIEVAL FROM NATIONAL DATA CENTER (NDC) REDUCING TIME AND I...IJCSEA Journal
Fast and efficient data management is one of the demanding technologies of today’s aspect. This paper
proposes a system which makes the working procedures of present manual system of storing and retrieving
huge citizen’s information of Bangladesh automated and increases its effectiveness. The implemented
search methodology is user friendly and efficient enough for high speed data retrieval ignoring spelling
error in the input keywords used for searching a particular citizen. The main concern in this research is
minimizing the total searching time for a given keyword. This can be done if we can pre-establish the idea
of getting the data belonging to the searching keyword. The primary and secondary key-code generated by
the Double Metaphone Algorithm for each word is used to establish that idea about the word. This
algorithm is used for creating the map of the original database, through which the keyword is matched
against the data.
Semantic Annotation Framework For Intelligent Information Retrieval Using KIM...dannyijwest
Due to the explosion of information/knowledge on the web and wide use of search engines for desired
information,the role of knowledge management(KM) is becoming more significant in an organization.
Knowledge Management in an Organization is used to create ,capture, store, share, retrieve and manage
information efficiently. The semantic web, an intelligent and meaningful web, tend to provide a promising
platform for knowledge management systems and vice versa, since they have the potential to give each
other the real substance for machine-understandable web resources which in turn will lead to an
intelligent, meaningful and efficient information retrieval on web. Today,the challenge for web community
is to integrate the distributed heterogeneous resources on web with an objective of an intelligent web
environment focusing on data semantics and user requirements. Semantic Annotation(SA) is being widely
used which is about assigning to the entities in the text and links to their semantic descriptions. Various
tools like KIM, Amaya etc may be used for semantic Annotation.
Framework for Product Recommandation for Review Datasetrahulmonikasharma
In the social networking era, product reviews have a significant influence on the purchase decisions of customers so the market has recognized this problem The problem with this is that the customers do not know how these systems work which results in trust issues. Therefore a different system is needed that helps customers with their need to process the information in product reviews. There are different approaches and algorithms of data filtering and recommendation .Most existing recommender systems were developed for commercial domains with millions of users. In this paper we have discussed the recommendation system and its related research and implemented different techniques of the recommender system .
INTELLIGENT SOCIAL NETWORKS MODEL BASED ON SEMANTIC TAG RANKINGdannyijwest
Social Networks has become one of the most popular platforms to allow users to communicate, and share their interests without being at the same geographical location. With the great and rapid growth of Social Media sites such as Facebook, LinkedIn, Twitter…etc. causes huge amount of user-generated content. Thus, the improvement in the information quality and integrity becomes a great challenge to all social media sites, which allows users to get the desired content or be linked to the best link relation using improved search / link technique. So introducing semantics to social networks will widen up the representation of the social networks. In this paper, a new model of social networks based on semantic tag ranking is introduced. This model is based on the concept of multi-agent systems. In this proposed model the representation of social links will be extended by the semantic relationships found in the vocabularies which are known as (tags) in most of social networks.The proposed model for the social media engine is based on enhanced Latent Dirichlet Allocation(E-LDA) as a semantic indexing algorithm, combined with Tag Rank as social network ranking algorithm. The improvements on (E-LDA) phase is done by optimizing (LDA) algorithm using the optimal parameters. Then a filter is introduced to enhance the final indexing output. In ranking phase, using Tag Rank based on the indexing phase has improved the output of the ranking. Simulation results of the proposed model have shown improvements in indexing and ranking output.
SENTIMENT ANALYSIS IN MYANMAR LANGUAGE USING CONVOLUTIONAL LSTM NEURAL NETWORKijnlc
In recent years, there has been an increasing use of social media among people in Myanmar and writing review on social media pages about the product, movie, and trip are also popular among people. Moreover, most of the people are going to find the review pages about the product they want to buy before deciding whether they should buy it or not. Extracting and receiving useful reviews over interesting products is very important and time consuming for people. Sentiment analysis is one of the important processes for extracting useful reviews of the products. In this paper, the Convolutional LSTM neural network architecture is proposed to analyse the sentiment classification of cosmetic reviews written in Myanmar Language. The paper also intends to build the cosmetic reviews dataset for deep learning and sentiment lexicon in Myanmar Language.
Sentiment Analysis In Myanmar Language Using Convolutional Lstm Neural Networkkevig
In recent years, there has been an increasing use of social media among people in Myanmar and writing
review on social media pages about the product, movie, and trip are also popular among people. Moreover,
most of the people are going to find the review pages about the product they want to buy before deciding
whether they should buy it or not. Extracting and receiving useful reviews over interesting products is very
important and time consuming for people. Sentiment analysis is one of the important processes for extracting
useful reviews of the products. In this paper, the Convolutional LSTM neural network architecture is
proposed to analyse the sentiment classification of cosmetic reviews written in Myanmar Language. The
paper also intends to build the cosmetic reviews dataset for deep learning and sentiment lexicon in Myanmar
Language.
Modeling the Adaption Rule in Contextaware Systemsijasuc
Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing
systems. Each context-aware application has its own set of behaviors to react to context modifications. This
paper is concerned with the context modeling and the development methodology for context-aware systems.
We proposed a rule-based approach and use the adaption tree to model the adaption rule of context-aware
systems. We illustrate this idea in an arithmetic game application.
Semantic Based Model for Text Document Clustering with IdiomsWaqas Tariq
Text document clustering has become an increasingly important problem in recent years because of the tremendous amount of unstructured data which is available in various forms in online forums such as the web, social networks, and other information networks. Clustering is a very powerful data mining technique to organize the large amount of information on the web. Traditionally, document clustering methods do not consider the semantic structure of the document. This paper addresses the task of developing an effective and efficient method to improve the semantic structure of the text documents. A method has been developed that performs the following: tag the documents for parsing, replacement of idioms with their original meaning, semantic weights calculation for document words and apply semantic grammar. The similarity measure is obtained between the documents and then the documents are clustered using Hierarchical clustering algorithm. The method adopted in this work is evaluated on different data sets with standard performance measures and the effectiveness of the method to develop in meaningful clusters has been proved.
Feature selection, optimization and clustering strategies of text documentsIJECEIAES
Clustering is one of the most researched areas of data mining applications in the contemporary literature. The need for efficient clustering is observed across wide sectors including consumer segmentation, categorization, shared filtering, document management, and indexing. The research of clustering task is to be performed prior to its adaptation in the text environment. Conventional approaches typically emphasized on the quantitative information where the selected features are numbers. Efforts also have been put forward for achieving efficient clustering in the context of categorical information where the selected features can assume nominal values. This manuscript presents an in-depth analysis of challenges of clustering in the text environment. Further, this paper also details prominent models proposed for clustering along with the pros and cons of each model. In addition, it also focuses on various latest developments in the clustering task in the social network and associated environments.
MODIFIED PAGE RANK ALGORITHM TO SOLVE AMBIGUITY OF POLYSEMOUS WORDSIJCI JOURNAL
Ambiguity in natural language has an effect on Information Retrieval (IR) system in general and web
search system in particular. Word sense ambiguity is the reason behind the poor performance of IR system.
If the ambiguous words are correctly disambiguated then IR performance can increase. WSD is defined as
the task of identifying the sense of word in textual context. Word Sense Disambiguation (WSD) is the
central problem of language processing. WSD improves the IR in many ways. Current IR system do not use
explicit WSD and rely on user typing enough content in the query to only retrieve documents relevant to the
intended senses. This paper proposes an algorithm for efficient retrieval of information on the Web
according to user’s need. Results are more accurate and they are according to user’s preference.
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.
Design of optimal search engine using text summarization through artificial i...TELKOMNIKA JOURNAL
Natural language processing is the trending topic in the latest research areas, which allows the developers to create the human-computer interactions to come into existence. The natural language processing is an integration of artificial intelligence, computer science and computer linguistics. The research towards natural Language Processing is focused on creating innovations towards creating the devices or machines which operates basing on the single command of a human. It allows various Bot creations to innovate the instructions from the mobile devices to control the physical devices by allowing the speech-tagging. In our paper, we design a search engine which not only displays the data according to user query but also performs the detailed display of the content or topic user is interested for using the summarization concept. We find the designed search engine is having optimal response time for the user queries by analyzing with number of transactions as inputs. Also, the result findings in the performance analysis show that the text summarization method has been an efficient way for improving the response time in the search engine optimizations.
Improving Sentiment Analysis of Short Informal Indonesian Product Reviews usi...TELKOMNIKA JOURNAL
Sentiment analysis in short informal texts like product reviews is more challenging. Short texts are
sparse, noisy, and lack of context information. Traditional text classification methods may not be suitable
for analyzing sentiment of short texts given all those difficulties. A common approach to overcome these
problems is to enrich the original texts with additional semantics to make it appear like a large document of
text. Then, traditional classification methods can be applied to it. In this study, we developed an automatic
sentiment analysis system of short informal Indonesian texts using Naïve Bayes and Synonym Based
Feature Expansion. The system consists of three main stages, preprocessing and normalization, features
expansion and classification. After preprocessing and normalization, we utilize Kateglo to find some
synonyms of every words in original texts and append them. Finally, the text is classified using Naïve
Bayes. The experiment shows that the proposed method can improve the performance of sentiment
analysis of short informal Indonesian product reviews. The best sentiment classification performance using
proposed feature expansion is obtained by accuracy of 98%.The experiment also show that feature
expansion will give higher improvement in small number of training data than in the large number of them.
Business intelligence analytics using sentiment analysis-a surveyIJECEIAES
Sentiment analysis (SA) is the study and analysis of sentiments, appraisals and impressions by people about entities, person, happening, topics and services. SA uses text analysis techniques and natural language processing methods to locate and extract information from big data. As most of the people are networked themselves through social websites, they use to express their sentiments through these websites.These sentiments are proved fruitful to an individual, business, government for making decisions. The impressions posted on different available sources are being used by organization to know the market mood about the services they are providing. Analyzing huge moods expressed with different features, style have raised challenge for users. This paper focuses on understanding the fundamentals of sentiment analysis, the techniques used for sentiment extraction and analysis. These techniques are then compared for accuracy, advantages and limitations. Based on the accuracy for expexted approach, we may use the suitable technique.
HIGH SPEED DATA RETRIEVAL FROM NATIONAL DATA CENTER (NDC) REDUCING TIME AND I...IJCSEA Journal
Fast and efficient data management is one of the demanding technologies of today’s aspect. This paper
proposes a system which makes the working procedures of present manual system of storing and retrieving
huge citizen’s information of Bangladesh automated and increases its effectiveness. The implemented
search methodology is user friendly and efficient enough for high speed data retrieval ignoring spelling
error in the input keywords used for searching a particular citizen. The main concern in this research is
minimizing the total searching time for a given keyword. This can be done if we can pre-establish the idea
of getting the data belonging to the searching keyword. The primary and secondary key-code generated by
the Double Metaphone Algorithm for each word is used to establish that idea about the word. This
algorithm is used for creating the map of the original database, through which the keyword is matched
against the data.
Semantic Annotation Framework For Intelligent Information Retrieval Using KIM...dannyijwest
Due to the explosion of information/knowledge on the web and wide use of search engines for desired
information,the role of knowledge management(KM) is becoming more significant in an organization.
Knowledge Management in an Organization is used to create ,capture, store, share, retrieve and manage
information efficiently. The semantic web, an intelligent and meaningful web, tend to provide a promising
platform for knowledge management systems and vice versa, since they have the potential to give each
other the real substance for machine-understandable web resources which in turn will lead to an
intelligent, meaningful and efficient information retrieval on web. Today,the challenge for web community
is to integrate the distributed heterogeneous resources on web with an objective of an intelligent web
environment focusing on data semantics and user requirements. Semantic Annotation(SA) is being widely
used which is about assigning to the entities in the text and links to their semantic descriptions. Various
tools like KIM, Amaya etc may be used for semantic Annotation.
Framework for Product Recommandation for Review Datasetrahulmonikasharma
In the social networking era, product reviews have a significant influence on the purchase decisions of customers so the market has recognized this problem The problem with this is that the customers do not know how these systems work which results in trust issues. Therefore a different system is needed that helps customers with their need to process the information in product reviews. There are different approaches and algorithms of data filtering and recommendation .Most existing recommender systems were developed for commercial domains with millions of users. In this paper we have discussed the recommendation system and its related research and implemented different techniques of the recommender system .
INTELLIGENT SOCIAL NETWORKS MODEL BASED ON SEMANTIC TAG RANKINGdannyijwest
Social Networks has become one of the most popular platforms to allow users to communicate, and share their interests without being at the same geographical location. With the great and rapid growth of Social Media sites such as Facebook, LinkedIn, Twitter…etc. causes huge amount of user-generated content. Thus, the improvement in the information quality and integrity becomes a great challenge to all social media sites, which allows users to get the desired content or be linked to the best link relation using improved search / link technique. So introducing semantics to social networks will widen up the representation of the social networks. In this paper, a new model of social networks based on semantic tag ranking is introduced. This model is based on the concept of multi-agent systems. In this proposed model the representation of social links will be extended by the semantic relationships found in the vocabularies which are known as (tags) in most of social networks.The proposed model for the social media engine is based on enhanced Latent Dirichlet Allocation(E-LDA) as a semantic indexing algorithm, combined with Tag Rank as social network ranking algorithm. The improvements on (E-LDA) phase is done by optimizing (LDA) algorithm using the optimal parameters. Then a filter is introduced to enhance the final indexing output. In ranking phase, using Tag Rank based on the indexing phase has improved the output of the ranking. Simulation results of the proposed model have shown improvements in indexing and ranking output.
SENTIMENT ANALYSIS IN MYANMAR LANGUAGE USING CONVOLUTIONAL LSTM NEURAL NETWORKijnlc
In recent years, there has been an increasing use of social media among people in Myanmar and writing review on social media pages about the product, movie, and trip are also popular among people. Moreover, most of the people are going to find the review pages about the product they want to buy before deciding whether they should buy it or not. Extracting and receiving useful reviews over interesting products is very important and time consuming for people. Sentiment analysis is one of the important processes for extracting useful reviews of the products. In this paper, the Convolutional LSTM neural network architecture is proposed to analyse the sentiment classification of cosmetic reviews written in Myanmar Language. The paper also intends to build the cosmetic reviews dataset for deep learning and sentiment lexicon in Myanmar Language.
Sentiment Analysis In Myanmar Language Using Convolutional Lstm Neural Networkkevig
In recent years, there has been an increasing use of social media among people in Myanmar and writing
review on social media pages about the product, movie, and trip are also popular among people. Moreover,
most of the people are going to find the review pages about the product they want to buy before deciding
whether they should buy it or not. Extracting and receiving useful reviews over interesting products is very
important and time consuming for people. Sentiment analysis is one of the important processes for extracting
useful reviews of the products. In this paper, the Convolutional LSTM neural network architecture is
proposed to analyse the sentiment classification of cosmetic reviews written in Myanmar Language. The
paper also intends to build the cosmetic reviews dataset for deep learning and sentiment lexicon in Myanmar
Language.
Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that focuses on the interaction between computers and human language. It encompasses a range of techniques and technologies that enable machines to understand, interpret, and generate human language in a way that is meaningful and useful.
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Conversational AI Agents have become mainstream today due to significant advancements in the methods required to build accurate models, such as machine learning and deep learning, and, secondly, because they are seen as a natural fit in a wide range of domains, such as healthcare, e-commerce, customer service, tourism, and education, that rely heavily on natural language conversations in day-to-day operations. This rapid increase in demand has been matched by an equally rapid rate of research and development, with new products being introduced on a daily basis.
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Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) and computational linguistics that focuses on enabling computers to understand and interact with human language. It combines techniques from computer science, linguistics, and statistics to bridge the gap between human language and machine understanding. NLP has gained significant attention in recent years due to advancements in AI and the increasing need for machines to process and interpret vast amounts of textual data.
For this project, we had to conduct research on a topic that was seen as a relevant area of study in Enterprise Systems and how it will be applicable in the future.
We chose to study the effects artificial intelligence will have on CRM systems. To view our findings, you can view the video here - https://www.youtube.com/watch?v=Fe55c60QPwY&t=9s
AI & Cognitive Computing are some of the most popular business an technical words out there. It is critical to get the basic understanding of Cognitive Computing, which helps us appreciate the technical possibilities and business benefits of the technology.
Building a recommendation system based on the job offers extracted from the w...IJECEIAES
Recruitment, or job search, is increasingly used throughout the world by a large population of users through various channels, such as websites, platforms, and professional networks. Given the large volume of information related to job descriptions and user profiles, it is complicated to appropriately match a user's profile with a job description, and vice versa. The job search approach has drawbacks since the job seeker needs to search a job offers in each recruitment platform, manage their accounts, and apply for the relevant job vacancies, which wastes considerable time and effort. The contribution of this research work is the construction of a recommendation system based on the job offers extracted from the web and on the e-portfolios of job seekers. After the extraction of the data, natural language processing is applied to structured data and is ready for filtering and analysis. The proposed system is a content-based system, it measures the degree of correspondence between the attributes of the e-portfolio with those of each job offer of the same list of competence specialties using the Euclidean distance, the result is classified with a decreasing way to display the most relevant to the least relevant job offers
TEXT SENTIMENTS FOR FORUMS HOTSPOT DETECTIONijistjournal
The user generated content on the web grows rapidly in this emergent information age. The evolutionary changes in technology make use of such information to capture only the user’s essence and finally the useful information are exposed to information seekers. Most of the existing research on text information processing, focuses in the factual domain rather than the opinion domain. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyses the forum text data and computes value for each word of text. The proposed approach combines K-means clustering and Support Vector Machine with PSO (SVM-PSO) classification algorithm that can be used to group the forums into two clusters forming hotspot forums and non-hotspot forums within the current time span. The proposed system accuracy is compared with the other classification algorithms such as Naïve Bayes, Decision tree and SVM. The experiment helps to identify that K-means and SVM-PSO together achieve highly consistent results.
Total Ionization Cross Sections due to Electron Impact of Ammonia from Thresh...Dr. Amarjeet Singh
In the present paper, we have employed modified Khare-BEB method [Atoms, (2019)] to evaluate total ionization cross sections by the electron impact for ammonia in energy range from the ionization threshold to 10 MeV. The theoretical ionization cross sections have been compared to the available previous theoretical and experimental results. The collision parameters dipole matrix squared M_j^2 and CRP also have been calculated. The present calculations were found in remarkable agreement with the available experimental results.
A Case Study on Small Town Big Player – Enjay IT Solutions Ltd., BhiladDr. Amarjeet Singh
Adequately trained Manpower is a problem that affects the IT industry as a whole, but it is particularly acute for Enjay IT Solution. Enjay's location in a semi-urban or rural area makes it even more difficult to find a talented employee with the right skills. As the competition for skilled workers grows, it becomes more difficult to attract and keep those workers who have the requisite training and experience.
Effect of Biopesticide from the Stems of Gossypium Arboreum on Pink Bollworm ...Dr. Amarjeet Singh
Pink bollworm and Lepidoptera development quickly in numbers which is a typical animal group that produces around 100 youthful ones inside certain days or weeks. This assault influences the harvests broadly in the tropical and sub-tropical temperature areas. Thus, to keep up with the yield of harvests the vermin ought to be kept away by utilizing pesticides. The unnecessary measure of the purpose of pesticides influences the dirt, land, and as well as human well-being, and contaminates the climate. Thus, an ozone-accommodating biopesticide is extracted from the stems of the Gossypium arboreum. Thus, the extraction of biopesticide from the stems of Gossypium arboreum demonstrated that the quantity of pink bollworm and Lepidoptera is diminished step by step in the wake of showering the arrangement on the impacted region of the plant because of the presence of the gossypol.
Artificial Intelligence Techniques in E-Commerce: The Possibility of Exploiti...Dr. Amarjeet Singh
E-Commerce has transformed business as we know over the past few decades. The rapid increasing use of the Internet and the strong purchasing power in Saudi Arabia have had a strong impact on the evolution of E-Commerce in the country. Saudi Arabia is yet another country that will release artificial intelligence power to fuel its growth in the economic world. Recently, artificial intelligence (AI) applications that can facilitate e-commerce processes have been widely used. The impact of using artificial intelligence (AI) concepts and techniques on the efficiency of e-commerce, particularly has been overlooked by many prior studies. In this paper, a literature review was conducted to explore and investigate possible applications of AI in E-Commerce that can help Saudi Arabian businesses.
Factors Influencing Ownership Pattern and its Impact on Corporate Performance...Dr. Amarjeet Singh
This study on factors influencing Ownership pattern and its impact on corporate performance has used five industries data viz Automobile industry, IT industry, Banking industry, Oil & Gas industry and pharmaceutical industry for five years from 2017 to 2021. First the factors influencing ownership pattern was identified and later its impact on corporate performance was analysed. Multiple Regression, ANOVA and Correlation was used in SPSS 28. Percentage of independent directors on the board and size of the company has significant impact on Indian Promotor holding and non-institutional ownership has significant impact on corporate performance.
An Analytical Study on Ratios Influencing Profitability of Selected Indian Au...Dr. Amarjeet Singh
Every country with a well-developed transportation network has a well-developed economy. The automobile industry is a critical engine of the nation's economic development. The automobile industry has significant backward and forward links with every area of the economy, as well as a strong and progressive multiplier impact. The automotive industry and the auto component industry are both included in the vehicle industry. It includes passenger waggons, light, medium, and heavy commercial vehicles, as well as multi-utility vehicles such as jeeps, three-wheelers, military vehicles, motorcycles, tractors, and auto-components such as engine parts, batteries, drive transmission parts, electrical, suspension and chassis parts, and body and other parts. In the last several years, India's automobile sector has seen incredible growth in sales, production, innovation, and exports. India's car industry has emerged as one of the best in the world, and the auto-ancillary sector is poised to assist the vehicle sector's expansion. Vehicle manufacturers and auto-parts manufacturers account for a significant component of global motorised manufacturing. Vehicle manufacturers from across the world are keeping a close eye on the Indian auto sector in order to assess future demand and establish India as a global manufacturing base. The current research focuses on three automotive behemoths: TATA Motors, MRF, and Mahindra & Mahindra.
A Study on Factors Influencing the Financial Performance Analysis Selected Pr...Dr. Amarjeet Singh
The growth of a country's banking sector has a significant impact on its economic development. The banking sector plays a critical role in determining a country's economic future. A well-planned, structured, efficient, and viable banking system is an essential component of an economy's economic and social infrastructure. In modern society, a strong banking system is required because it meets the financial needs of the modern society. In a country's economy, the banking system plays a crucial role. Because it connects surplus and deficit economic agents, the bank is the most important financial intermediary in the economy. The banking system is regarded as the economy's lifeline. It meets the financial needs of commerce, industry, and agriculture. As a result, the country's development and the banking system are intertwined. They are critical in the mobilisation of savings and the distribution of credit to various sectors of the economy. India's private sector banks play a critical role in the country's economic development. So The financial performance of private sector banks must be evaluated carefully.
An Empirical Analysis of Financial Performance of Selected Oil Exploration an...Dr. Amarjeet Singh
After the United States, China, and Japan, India was the world's fourth biggest consumer of oil and petroleum products. The nation is significantly reliant on crude oil imports, the majority of which come from the Middle East. The Indian oil and gas business is one of the country's six main sectors, with important forward links to the rest of the economy. More than two-thirds of the country's overall primary energy demands are met by the oil and gas industry. The industry has played a key role in placing India on the global map. India is now the world's sixth biggest crude oil user and ninth largest crude oil importer. In addition, the country's portion of the worldwide refining market is growing. India's refining industry is now the world's sixth biggest. With plans for Reliance Petroleum Limited to commission another refinery with a capacity of 29 MTPA next 16 to its 33 MTPA refinery in Jamnagar, Gujarat, this position is projected to be enhanced. As a consequence, the Reliance refinery would be the biggest single-site refinery in the world. Based on secondary data gathered from CMIE, the current research examines the ratios influencing the profitability of selected oil exploration and production businesses in India during a 10-year period.
Since 1991, thanks to economic policy liberalization, the Indian economy has entered an era in which Indian businesses can no longer disregard global markets. Prior to the 1990s, the prices of a variety of commodities, metals, and other assets were carefully regulated. Others, which were not rolled, were primarily dependant on regulated input costs. As a result, there was no uncertainty and, as a result, no price fluctuations. However, in 1991, when the process of deregulation began, the prices of most items were deregulated. It has also resulted in the exchange being partially deregulated, easing trade restrictions, lowering interest rates, and making significant advancements in foreign institutional investors' access to the capital markets, as well as establishing market-based government securities pricing, among other things. Furthermore, portfolio and securities price volatility and instability were influenced by market-determined exchange rates and interest rates. As a result, hedging strategies employing a variety of derivatives were exposed to a variety of risks. The Indian capital market will be examined in this study, with a focus on derivatives.
Theoretical Estimation of CO2 Compression and Transport Costs for an hypothet...Dr. Amarjeet Singh
SEI S.p.a. presented a project to build a 1320 MW coal-fired power plant in Saline Joniche, on the Southern tip of Calabria Region, Italy, in 2008. A gross early evaluation about the possibility to add CCS (CO2 Capture & Storage) was performed too. The project generated widespread opposition among environmental associations, citizens and local institutions in that period, against the coal use to produce energy, as a consequence of its GHG clima-alterating impact. Moreover the CCS (also named Carbon Capture & Storage or more recently CCUS: Carbon Capture-Usage-Storage) technology was at that time still an unknown and “mysterious” solution for the GHG avoiding to the atmosphere. The present study concerns the sizing of the compression and transportation system of the CCS section, included in the project presented at the time by SEI Spa; the sizing of the compression station and the pipeline connecting the plant to the possible Fosca01 offshore injection site previously studied as a possible storage solution, as part of a coarse screening of CO2 storage sites in the Calabria Region. This study takes into account the costs of construction, operation and maintenance (O&M) of both the compression plant and the sound pipeline, considering the gross static storage capacity of the Fosca01 reservoir as a whole as previously evaluated.
Analytical Mechanics of Magnetic Particles Suspended in Magnetorheological FluidDr. Amarjeet Singh
In this paper, the behavior of MR particles has been systematically investigated within the scope of analytical mechanics. . A magnetorheological fluid belongs to a class of smart materials. In magnetorheological fluids, the motion of magnetic particles is controlled by the action of internal and external forces. This paper presents analytical mechanics for the interaction of system of particles in MR fluid. In this paper, basic principles of Analytical Mechanics are utilized for the construction of equations.
Techno-Economic Aspects of Solid Food Wastes into Bio-ManureDr. Amarjeet Singh
Solid waste is health hazard and cause damage to the environment due to improper handling. Solid waste comprises of Industrial Waste (IW), Hazardous Waste (HW), Municipal Solid Waste (MSW), Electronic waste (E-waste), Bio-Medical Waste (BMW) which depend on their supply & characteristics. Food waste or Bio-waste composting and its role in sustainable development is explained in food waste is a growing area of concern with many costs to our community in terms of waste collection, disposal and greenhouse gases. When rotting food ends up in landfill it turns into methane, a greenhouse gas that is particularly damaging to the environment. Composting is biochemical process in which organic materials are biologically degraded, resulting in the production of organic by products and energy in the form of heat. Heat is trapped within the composting mass, leading to the phenomenon of self-heating. This overall process provide us Bio-Manure.
Crypto-Currencies: Can Investors Rely on them as Investment Avenue?Dr. Amarjeet Singh
The purpose of this study is to examine investors’ perceptions about investing in crypto-currencies. We think that investors trust in crypto-currencies is largely driven by crypto-currency comprehension, trust in government, and transaction speed. This is the first study to examine crypto-currencies from the investor’s perspective. Following that, we discover important antecedents of crypto-currency confidence. Second, we look at the government's role in crypto-currencies. The importance of this study is: first, crypto-currencies have the potential to disrupt the current economic system as the debate is all about impact of decentralization of transactions; thus, further research into how it affects investors trust is essential; and second, access to crypto-currencies. Finally, if Fin-Tech companies or banks want to enter the bitcoin industry may not attract huge advertising costs as well as marketing to soothe clients' concerns about investing in various digital currencies The research sheds light on indecisiveness in the context of marketing aspects adopted by demonstrating investors are aware about the crypto.
Awareness of Disaster Risk Reduction (DRR) among Student of the Catanduanes S...Dr. Amarjeet Singh
The Island Province of Catanduanes is prone to all types of natural hazards that includes torrential and heavy rains, strong winds and surge, flooding and landslide or slope failures as a result of its geographical location and topography. RA 10121 mandates local DRRM bodies to “encourage community, specifically the youth, participation in disaster risk reduction and management activities, such as organizing quick response groups, particularly in identified disaster-prone areas, as well as the inclusion of disaster risk reduction and management programs as part of youth programs and projects. The study aims to determine the awareness to disaster of the student of the Catanduanes State University. The disaster-based questionnaire was prepared and distributed among 636 students selected randomly from different Colleges and Laboratory Schools in the University
The Catanduanes State University students understood some disaster-related concepts and ideas, but uncertain on issues on preparedness, adaptation, and awareness on the risks inflicted by these natural hazards. Low perception on disaster risks are evidently observed among students. The responses of the students could be based on the efficiency and impact of the integration of DRR education in the senior high school curriculum. Specifically, integration of the concepts about the hazards, hazard maps, disaster preparedness, awareness, mitigation, prevention, adaptation, and resiliency in the science curriculum possibly affect the knowledge and understanding of students on DRR. Preparedness drills and other forms of capacity building must be done to improve awareness of the student towards DRRM.
The study further recommends that teachers and instructor must also be capacitated in handling disaster as they are the prime movers in the implementation of the DRRM in education. Preparedness drills and other forms of capacity building must be done to improve awareness of the student towards DRRM. Core subjects in Earth Sciences must be reinforced with geologic hazards. Learning competencies must also be focused on hazard identification and mapping, and coping with different geologic disaster.
The 1857 war was a watershed moment in the history of the Indian subcontinent. The battle has sparked academic debate among historians and sociologists all around the world. Despite the fact that it has been more than 150 years, this battle continues to pique the interest of historians. The war's causes and events that occurred throughout the conflict, persons who backed the British and anti-British fighters, and the results and ramifications, are all aspects of this conflict. In terms of outcomes, many academics believe that the war was a failure for those who started it. It is often assumed that the Indians who battled the British in this conflict were unable to achieve their goals. Many gains accrued to Indians as a result of the conflict, but these achievements are overshadowed by the dispute over the war's failure. This research effort focuses on the war's achievements for India, and the significance of those achievements.
Haryana's Honour Killings: A Social and Legal Point of ViewDr. Amarjeet Singh
Life is unpredictably unpredictable. Nobody knows what will happen in the next minute of their lives. In this circumstance, every human being has the right and desire to conduct their lives according to their own desires. No one should be forced to live a life solely for the benefit and reputation of others. Honour killing is defined as the assassination of a person, whether male or female, who refuses to accept the family's arranged marriage or decides to move her or his marital life according to her or his wishes solely because it jeopardizes the family's honour. The family's supreme authority looks after the family's name but neglects to consider the love and affection shared among family members. I have discussed honour killing in India in my research work. This sort of murder occurs as a result of particular triggers, which are also examined in relation to the role of the law in honour killing. No one can be released free if they break the law, and in this case, it is a felony that violates various regulations designed to safeguard citizens. This crime is similar to many others, but it is distinct enough to be differentiated in the report. When the husband is of low social standing, it lowers the position and caste of the female family, prompting the male family members to murder the girl. But they forget that the girl is their kid and that while rank may be attained, a girl's life can never be replaced, and that caste is less valuable than the girl's life and love spent with them.
Optimization of Digital-Based MSME E-Commerce: Challenges and Opportunities i...Dr. Amarjeet Singh
The impact caused by the Covid-19 Pandemic on Micro and Small and Medium Enterprises (MSMEs) was so severe and fatal
that not a few went out of business. The heavy burden is borne by MSME actors due to social restrictions imposed by the
government, the declining purchasing power of the people, a product that continues to decline until capital runs out. Plus
inadequate knowledge in carrying out marketing strategies and product innovations are the main trigger for the lack of
enthusiasm for MSME actors as well as bankruptcy. MSME digitalization-based e-commerce is an opportunity and the right
solution in dealing with the obstacles caused by the impact of Covid-19, as well as a challenge for MSME actors to design old
ways in new ways through digital business.
Modal Space Controller for Hydraulically Driven Six Degree of Freedom Paralle...Dr. Amarjeet Singh
This paper presents the Modal space decoupled control for a hydraulically driven parallel mechanism has been presented. The approach is based on singular values decomposition to the properties of joint-space inverse mass matrix, and mapping of the control and feedback variables from the joint space to the decoupling modal space. The method transformed highly coupled six-input six-output dynamics into six independent single-input single-output (SISO) 1 DOF hydraulically driven mechanical systems. The novelty in this method is that the signals including control errors, control outputs and pressure feedbacks are transformed into decoupled modal space and also the proportional gains and dynamic pressure feedback are tuned in modal space. The results indicate that the conventional controller can only attenuate the resonance peaks of the lower eigenfrequencies of six rigid modes properly, and the peaking points of other relative higher eigenfrequencies are over damped, The further results show that it is very effective to design and tune the system in modal space and that the bandwidth increased substantially except surge (x) and sway (y) motions, each degree of freedom can be almost tuned independently and their bandwidths can be increased near to the undamped eigenfrequencies.
It is a known fact that a large number of Steel Industry Expansion projects in India have been delayed due to regulatory clearances, environmental issues and problems pertaining to land acquisition. Also, there are challenges in the tendering phase that affect viability of projects thus delaying implementation, construction phase is beset with over-runs and disputes and last but not the least; provider skills are weak all across the value chain. Given the critical role of Steel Sector in ensuring a sustained growth trajectory for India, it is imperative that we identify the core issues affecting completion of infrastructure projects in India and chalk out initiatives that need to be acted upon in short term as well as long term.
A blockchain is a decentralised database that is shared across computer network nodes. A blockchain acts as a database, storing information in a digital format. The study primarily aims to explore how in the future, block chain technology will alter several areas of the Indian economy. The current study aims to obtain a deeper understanding of blockchain technology's idea and implementation in India, as well as the technology's potential as a disruptive financial technological innovation.
Secondary sources such as reports, journals, papers, and websites were used to compile all the data. Current and relevant information were utilised to help understand the research goals. All the information is rationally organised to fulfil the objectives. The current research focuses on recommendations for enhancing India's Blockchain ecosystem so that it may become one of the best in the world at utilising this new technology.
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.
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.
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
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.
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.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
1. International Journal of Engineering and Management Research e-ISSN: 2250-0758 | p-ISSN: 2394-6962
Volume-11, Issue-3 (June 2021)
www.ijemr.net https://doi.org/10.31033/ijemr.11.3.21
124 This Work is under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Financial Tracker using NLP
Kartik Baliyan1
, Shubham Vishnoi2
and Dr. Swati Sharma3
1
Student, Department of Information Technology, MIET College, Meerut, INDIA
2
Student, Department of Information Technology, MIET College, Meerut, INDIA
3
Associate Professor & Head, Department of Information Technology, MIET College, Meerut, INDIA
1
Corresponding Author: dhurav1997@gmail.com
ABSTRACT
NLP (Natural Language Processing) is a mechanism
that helps computers to know natural languages like English.
In general, computers can understand data, tables etc. which
are well formed. But when it involves natural
languages, it's unacceptable for computers to spot them. NLP
helps to translate the tongue in such a fashion which will be
easily processed by modern computers. Financial Tracker is
an approach which will use NLP as a tool and
can differentiate the user messages in various categories. the
appliance of the approach will be seen at multiple levels. At a
personal level, this permits users to filtrate useful financial
messages from an large junk of text messages. On the
opposite hand, from an industrial point of view, this can
be useful in services like online loan disbursal, which are
hitting the market nowadays. These services attempt
to provide online loans to individuals in an exceedingly faster
and quicker manner. But when it involves business view, loan
recovery from customers becomes a really important &
crucial aspect. As most such services can’t take strict legal
actions against the fraud customers, it becomes a requirement
that loan should be provided only to those customers who
deserve it. At that time, this model can come under the image.
As a business we will find the user’s messages from their
inbox (after taking permission from the users). These
messages are often filtered using NLP which might help to
differentiate various types of messages within the user's
inbox which might further be used as a content for further
prediction and analysis on user’s behaviour in terms of
cash related transactions.
Keywords— Supervised Learning, Text Classification,
Machine Learning, Classification, Regex
I. INTRODUCTION
Natural Language Processing has become a very
important application of machine learning. Machine
learning is traditionally very famous for its prediction and
classification algorithms. NLP also uses these features of
machine learning to realize insights on textual data, build
correlations etc which is employed to process the human
language efficiently. in line with various estimations, very
less of the available data is present in structured form. We
all are surrounded by data. Data is being generated as we
speak, as we tweet, as we send various messages on
whatsapp and in various other activities. Most of this data
exists within the text form, which is very unstructured in
nature. whether or not we've high dimensional data, the
data present in it cannot be directly used
unless it's processed (read and understood) manually or
analyzed by a computing system. The approach discussed
here is employed to unravel this problem of
text processing by automated computers and use the results
for prediction. The civil score generator is an inspiration to
use NLP in user’s messages processing which
might be employed by organizations that provide online
loans to the shoppers who don't have any credit history and
hence no civil score data. This method can help to get an
estimated civil score with the assistance of a pre-processed
NLP model, which classifies user’s inbox messages as
credit-amount, debit-amount, and recharge- amount
messages which may help to predict the monthly
expenditure, earning and lifestyle of the individual
II. EXPERIMENT AND RESULT
In this research, we've got collected sample messages for
building information that was preprocessed for further
actions. The filtration process involves following steps
● Text Transformation to lower case character.
● Removal of unwanted symbols, stop words from
text using regex. These stop words include words like
(“the”, “a”, “an”, “in”), which might be ignored easily
with little or no or no loss of knowledge
● Stemming - It stems the words to seek out the
basis word. for instance, a collection of words (classifier,
classifies, classify) are going to be stemmed to the word
classify.
All the above steps are a part of NLP data pre-
processing. of these steps make the information lighter and
fewer noisy. Then, the information was converted to the
matrix which contains all the various words within
the data because the attribute name and every sentence (or
text message) as a row. Each cell contains either a zero or
one supported the presence of the word within the specific
sentence. we've got used count vectorizer from Sklearn for
this task. the information is now within the form which
might be processed by a computing system. Then,
resampling is finished to resample various sorts
of messages to handle multiple output class
imbalance within the data. Then with the assistance of
random forest classification algorithms from machine
learning, various messages are classified in specified
categories for further analysis. Random forest, because
the name implies, consists of the many individual decision
2. International Journal of Engineering and Management Research e-ISSN: 2250-0758 | p-ISSN: 2394-6962
Volume-11, Issue-3 (June 2021)
www.ijemr.net https://doi.org/10.31033/ijemr.11.3.21
125 This Work is under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
trees that employment as an ensemble (collection of
decision trees). Each decision tree within the random forest
brings out a category prediction and also the class with the
foremost votes become the model’s prediction.
After Message classification, different messages
are explore for the message genre which helps to predict
monthly expenditure and earnings of a private at one place.
Figure 1: Flowchart
III. CONCLUSION
In this study, we've found a really useful application of
NLP from text messages. Such a content and data are
often used for an unlimited number of studies within
the field of NLP. This model are often very useful in
sectors like banking, e- commerce together with its
significance within the personal life for budget
management.
REFERENCES
[1] Ingrid E. Fisher, Margaret R. Garnsey, & Mark E.
Hughes. (2016). Natural language processing in
accounting, auditing and finance: A synthesis of the
literature with a roadmap for future research. DOI:
10.1002/isaf.1386.
[2] Venera Arnaoudova, Sonia Haiduc, Andrian Marcus, &
Giuliano Antoniol. (2015). The use of text retrieval and
natural language processing in software engineering. DOI:
10.1145/2889160.2891053.
[3] Tushar Ghorpade & Lata Ragha. (2012). Featured
based sentiment classification for hotel reviews using NLP
and Bayesian classification.
DOI: 10.1109/ICCICT.2012.6398136.
[4] Monisha Kanakaraj & Ram Mohana Reddy Guddeti.
(2015). Performance analysis of Ensemble methods on
Twitter sentiment analysis using NLP techniques. DOI:
10.1109/ICOSC.2015.7050801.
[5] Shweta C. Dharmadhikari, Maya Ingle, & Parag
Kulkarni. (2011). Empirical studies on machine learning
based textclassification algorithms.
DOI: 10.5121/acij.2011.2615.
[6] Gobinda G. Chowdhury. (2005). Natural language
processing. DOI: 10.1002/aris.1440370103.
[7] Erik Cambria & Bebo White. (2014). A review of
natural language processing research.
DOI: 10.1109/MCI.2014.2307227
[8] Prakash M Nadkarni, Lucila Ohno-Machado, & Wendy
W Chapman. (2011). Natural language processing: an
introduction. DOI: 10.1136/amiajnl-2011-000464.
[9] Rui Xia, Chengqing Zong, & Shoushan Li. (2011).
Ensemble of feature sets and classification algorithms for
sentiment classification. DOI: 10.1016/j.ins.2010.11.023.
[10] Atefeh Farzindar & Diana Inkpen. (2015). Natural
language processing for social media.
DOI: 10.2200/S00659ED1V01Y201508HLT030.
[11] E. Stamatatos, N. Fakotakis, & G. Kokkinakis. (2000).
Text genre detection using common word frequencies.
DOI: 10.3115/992730.992763.
[12] Ellen Riloff & Wendy Lehnert. (1994). Information
extraction as a basis for high-precision text classification.
DOI: 10.1145/183422.183428.
[13] Teresa Gonçalves & Paulo Quaresma. (2004). The
impact of NLP techniques in the multilabel text
classification problem.
DOI: 10.1007/978-3-540-39985-8_46.
[14] Andronicus A. Akinyelu, Aderemi & O. Adewumi.
(2014). Classification of phishing email using random
forest machine learning technique.
DOI: 10.1155/2014/425731.
[15] Olga Ormandjieva, Ishrar Hussain, & Leila Kosseim.
(2007). Toward a text classification system for the quality
assessment of software requirements written in natural
language. DOI: 10.1145/1295074.1295082.