This document discusses a novel approach for opinion mining from online reviews based on a word alignment model. The approach regards identifying opinion relations as an alignment process, and then uses a graph-based co-ranking algorithm to estimate confidence for candidate relations. The word alignment model effectively reduces parsing errors compared to syntax-based methods, and the co-ranking algorithm decreases the probability of error propagation. Experimental results show the proposed model achieves better precision than traditional unsupervised alignment models in extracting opinion targets and words from reviews.
USING NLP APPROACH FOR ANALYZING CUSTOMER REVIEWScsandit
The Web considers one of the main sources of customer opinions and reviews which they are represented in two formats; structured data (numeric ratings) and unstructured data (textual comments). Millions of textual comments about goods and services are posted on the web by customers and every day thousands are added, make it a big challenge to read and understand them to make them a useful structured data for customers and decision makers. Sentiment
analysis or Opinion mining is a popular technique for summarizing and analyzing those opinions and reviews. In this paper, we use natural language processing techniques to generate some rules to help us understand customer opinions and reviews (textual comments) written in the Arabic language for the purpose of understanding each one of them and then convert them to a structured data. We use adjectives as a key point to highlight important information in the text then we work around them to tag attributes that describe the subject of the reviews, and we associate them with their values (adjectives).
An Analysis Of Research Paper " ‘A Literature Review On The Studies Of Internet Retailing Management’
Tao Zhang, Guijun Zhuang, Yuanyuan Huang
School of Management, Xi’an Jiaotong University, Xi’an, China" By students of ITM Bussiness School, Navi Mumbai, India.
Includes
What is Internet retailing?
Internet Retailing Strategy
Incentives for firms to adopt Internet retailing
Factor affecting Internet retailing adoption
Online business model and marketing strategy
Multi-Channel Management
Online Merchandise Management
How to design with science and not destroy the magicJoe Leech
By @mrjoe http://mrjoe.uk
The poet John Keats famously blamed scientists experimenting with light for 'unweaving the magic of the rainbow'.
Joe will look at applying science to design to make our apps and websites better.
We'll look at different types of data, from user research and analytics, to psychology. How to research, collect, source, asses and most importantly design using data without losing the magic.
USING NLP APPROACH FOR ANALYZING CUSTOMER REVIEWScsandit
The Web considers one of the main sources of customer opinions and reviews which they are represented in two formats; structured data (numeric ratings) and unstructured data (textual comments). Millions of textual comments about goods and services are posted on the web by customers and every day thousands are added, make it a big challenge to read and understand them to make them a useful structured data for customers and decision makers. Sentiment
analysis or Opinion mining is a popular technique for summarizing and analyzing those opinions and reviews. In this paper, we use natural language processing techniques to generate some rules to help us understand customer opinions and reviews (textual comments) written in the Arabic language for the purpose of understanding each one of them and then convert them to a structured data. We use adjectives as a key point to highlight important information in the text then we work around them to tag attributes that describe the subject of the reviews, and we associate them with their values (adjectives).
An Analysis Of Research Paper " ‘A Literature Review On The Studies Of Internet Retailing Management’
Tao Zhang, Guijun Zhuang, Yuanyuan Huang
School of Management, Xi’an Jiaotong University, Xi’an, China" By students of ITM Bussiness School, Navi Mumbai, India.
Includes
What is Internet retailing?
Internet Retailing Strategy
Incentives for firms to adopt Internet retailing
Factor affecting Internet retailing adoption
Online business model and marketing strategy
Multi-Channel Management
Online Merchandise Management
How to design with science and not destroy the magicJoe Leech
By @mrjoe http://mrjoe.uk
The poet John Keats famously blamed scientists experimenting with light for 'unweaving the magic of the rainbow'.
Joe will look at applying science to design to make our apps and websites better.
We'll look at different types of data, from user research and analytics, to psychology. How to research, collect, source, asses and most importantly design using data without losing the magic.
The talk has three parts : the first part gives an overview of data science work, including roadmap of data science team, responsibility and value of data scientists; the second part talks about pitfalls in analysis and teaches some common analysis methods; the third part takes decision support, metrics and AB testing as examples to explain the data science work and how they are translated to business value.
Offering A Model Of Evaluation Of Trust Suggesting Between Customers And E-St...Waqas Tariq
to succeed in the e-commerce depends on lots of factors; one of the important and vital ones is trust. In this Paper, we will suggest a model of Fuzzy Logical System which depicts some of the hidden relationships between the critical factors such as security, familiarity, and designing in a B2C commercial website on the one hand, and the competitive factor to other competitors on the other hand. We are going to find the impact of these factors on the decision-making process of people to buy through the B2C commercial websites, and we also will analyze how these factors influence the results of the B2C trading. The study also provides a device to sellers in order to improve their commercial websites; in addition, it provides on-line customers a helping device to buy through the commercial websites. In the study, the sample in the first questionnaire was the investigation of experts of e-commerce, and in the second one was the customers of commercial websites. Also, we have used the Expert Choice software to determine the priority of factors in the first questionnaire, and the SPSS and Excel software for sampling and analysis procedures to find the Fuzzy rules. Finally, we used the Fuzzy logical kit in the MATLAB software to analyze the factors which generate the model.
With the rapid growth in ecommerce, reviews for popular products on the web have grown rapidly.
Although these reviews are important for making decisions, it is difficult to read all the reviews.
Automating the opinion mining process was identified as a solution for the problem. Although there are
algorithms for opinion mining, an algorithm with better accuracy is needed. A feature and smiley based
algorithm was developed which extracts product features from reviews based on feature frequency and
generates an opinion summary based on product features.
The algorithm was tested on downloaded customer reviews. The sentences were tagged, opinion words
were extracted and opinion orientations were identified using semantic orientation of opinion words and
smileys. Since the precision values for feature extraction and both precision and recall values for opinion
orientation identification were improved by the new algorithm, it is more successful in opinion mining of
customer reviews.
Predicting the Next News Trends: The Advent of Intelligent Media AnalysisVMS
Predicting the Next News Trends: The Advent of Intelligent Media Analysis - a presentation given by Angela Jeffrey, APR, Vice President Integrated Media for VMS, at the 2010 PRSA International Conference in Washington D.C.
SENTIMENT ANALYSIS ON PRODUCT FEATURES BASED ON LEXICON APPROACH USING NATURA...ijnlc
Sentiment analysis has played an important role in identifying what other people think and what their behavior is. Text can be used to analyze the sentiment and classified as positive, negative or neutral. Applying the sentiment analysis on the product reviews on e-market helps not only the customer but also the industry people for taking decision. The method which provides sentiment analysis about the individual product’s features is discussed here. This paper presents the use of Natural Language Processing and SentiWordNet in this interesting application in Python: 1. Sentiment Analysis on Product review [Domain: Electronic]2. sentiment analysis regarding the product’s feature present in the product review [Sub Domain: Mobile Phones]. It usesa lexicon based approach in which text is tokenized for calculating the sentiment analysis of the product reviews on a e-market. The first part of paper includessentiment analyzer whichclassifiesthe sentiment present in product reviews into positive, negative or neutral depending on the polarity. The second part of the paper is an extension to the first part in which the customer review’s containing product’s features will be segregated and then these separated reviews are classified into positive, negative and neutral using sentiment analysis. Here, mobile phones are used as the product with features as screen, processors, etc. This gives a business solution for users and industries for effective product decisions.
The big story behind your big data: Six Practices for Making an Impact with T...Joachim B. Lyon
Text analytics is a powerful technology for drawing out compelling stories and deep insights from millions of customer comments. This study of strategic practices in 12 innovative companies show how customer experience (CX) professionals are using text analytics to change the way they work -- leveraging the customer’s voice to drive innovation and change, and becoming strategic business partners within their organizations.
Data collection options fit particular cultural context. In this presentation by WAC Survey and Strategic Research, market research techniques are looked at in relation to the cultural context of China.
Most of us use e-shopping (Any product) these days and refer its rating or reviews before we download or buy that product. Amazon/Play store provide a great number of products but unfortunately few of those product reviews are fraud. Hence such products must be marked, so that they will be recognizable for rest of the users. Here we are comparing reviews from two sites so that we can get more clear idea. We can get higher probability of getting real reviews if we take data from multiple sites. We are proposing a system to develop an android application that will take reviews from two different websites for single product, and analyze them with NLP for positive or negative rating. In this, user will give two different URLs of two different sites for same product to the system as input. For every URL reviews and comments will be fetched separately and analyzed with NLP for positive negative rating. Then their rating will be combined together with average to give final rating for the product. As we are handling the big data here, we are using Hadoops map reduce. So it will be easier to decide which product reviews are fraud or not.
The talk has three parts : the first part gives an overview of data science work, including roadmap of data science team, responsibility and value of data scientists; the second part talks about pitfalls in analysis and teaches some common analysis methods; the third part takes decision support, metrics and AB testing as examples to explain the data science work and how they are translated to business value.
Offering A Model Of Evaluation Of Trust Suggesting Between Customers And E-St...Waqas Tariq
to succeed in the e-commerce depends on lots of factors; one of the important and vital ones is trust. In this Paper, we will suggest a model of Fuzzy Logical System which depicts some of the hidden relationships between the critical factors such as security, familiarity, and designing in a B2C commercial website on the one hand, and the competitive factor to other competitors on the other hand. We are going to find the impact of these factors on the decision-making process of people to buy through the B2C commercial websites, and we also will analyze how these factors influence the results of the B2C trading. The study also provides a device to sellers in order to improve their commercial websites; in addition, it provides on-line customers a helping device to buy through the commercial websites. In the study, the sample in the first questionnaire was the investigation of experts of e-commerce, and in the second one was the customers of commercial websites. Also, we have used the Expert Choice software to determine the priority of factors in the first questionnaire, and the SPSS and Excel software for sampling and analysis procedures to find the Fuzzy rules. Finally, we used the Fuzzy logical kit in the MATLAB software to analyze the factors which generate the model.
With the rapid growth in ecommerce, reviews for popular products on the web have grown rapidly.
Although these reviews are important for making decisions, it is difficult to read all the reviews.
Automating the opinion mining process was identified as a solution for the problem. Although there are
algorithms for opinion mining, an algorithm with better accuracy is needed. A feature and smiley based
algorithm was developed which extracts product features from reviews based on feature frequency and
generates an opinion summary based on product features.
The algorithm was tested on downloaded customer reviews. The sentences were tagged, opinion words
were extracted and opinion orientations were identified using semantic orientation of opinion words and
smileys. Since the precision values for feature extraction and both precision and recall values for opinion
orientation identification were improved by the new algorithm, it is more successful in opinion mining of
customer reviews.
Predicting the Next News Trends: The Advent of Intelligent Media AnalysisVMS
Predicting the Next News Trends: The Advent of Intelligent Media Analysis - a presentation given by Angela Jeffrey, APR, Vice President Integrated Media for VMS, at the 2010 PRSA International Conference in Washington D.C.
SENTIMENT ANALYSIS ON PRODUCT FEATURES BASED ON LEXICON APPROACH USING NATURA...ijnlc
Sentiment analysis has played an important role in identifying what other people think and what their behavior is. Text can be used to analyze the sentiment and classified as positive, negative or neutral. Applying the sentiment analysis on the product reviews on e-market helps not only the customer but also the industry people for taking decision. The method which provides sentiment analysis about the individual product’s features is discussed here. This paper presents the use of Natural Language Processing and SentiWordNet in this interesting application in Python: 1. Sentiment Analysis on Product review [Domain: Electronic]2. sentiment analysis regarding the product’s feature present in the product review [Sub Domain: Mobile Phones]. It usesa lexicon based approach in which text is tokenized for calculating the sentiment analysis of the product reviews on a e-market. The first part of paper includessentiment analyzer whichclassifiesthe sentiment present in product reviews into positive, negative or neutral depending on the polarity. The second part of the paper is an extension to the first part in which the customer review’s containing product’s features will be segregated and then these separated reviews are classified into positive, negative and neutral using sentiment analysis. Here, mobile phones are used as the product with features as screen, processors, etc. This gives a business solution for users and industries for effective product decisions.
The big story behind your big data: Six Practices for Making an Impact with T...Joachim B. Lyon
Text analytics is a powerful technology for drawing out compelling stories and deep insights from millions of customer comments. This study of strategic practices in 12 innovative companies show how customer experience (CX) professionals are using text analytics to change the way they work -- leveraging the customer’s voice to drive innovation and change, and becoming strategic business partners within their organizations.
Data collection options fit particular cultural context. In this presentation by WAC Survey and Strategic Research, market research techniques are looked at in relation to the cultural context of China.
Most of us use e-shopping (Any product) these days and refer its rating or reviews before we download or buy that product. Amazon/Play store provide a great number of products but unfortunately few of those product reviews are fraud. Hence such products must be marked, so that they will be recognizable for rest of the users. Here we are comparing reviews from two sites so that we can get more clear idea. We can get higher probability of getting real reviews if we take data from multiple sites. We are proposing a system to develop an android application that will take reviews from two different websites for single product, and analyze them with NLP for positive or negative rating. In this, user will give two different URLs of two different sites for same product to the system as input. For every URL reviews and comments will be fetched separately and analyzed with NLP for positive negative rating. Then their rating will be combined together with average to give final rating for the product. As we are handling the big data here, we are using Hadoops map reduce. So it will be easier to decide which product reviews are fraud or not.
leewayhertz.com-AI in market research Charting a course from raw data to stra...KristiLBurns
AI in market research involves integrating Machine Learning (ML) algorithms into traditional methods, such as interviews, discussions, and surveys, to enhance the research process.
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.
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.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
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.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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