UMW: A model for enhancement in wearable technology based on opinion mining technique

2015 ◽  
Author(s):  
Shahab Saquib Sohail ◽  
Jamshed Siddiqui ◽  
Rashid Ali
Keyword(s):  
Opinion Mining ◽  
Wearable Technology ◽  
Mining Technique

A hybrid recommender system for the mining of consumer preferences from their reviews

2019 ◽  
Vol 46 (5) ◽  
pp. 664-682
Author(s):  
Li Chen Cheng ◽  
Ming-Chan Lin
Keyword(s):  
Opinion Mining ◽  
Information Overload ◽  
Consumer Preferences ◽  
Online Reviews ◽  
User Generated Content ◽  
Mining Technique ◽  
Movie Recommendation ◽  
Hybrid Recommender System ◽  
Hybrid Recommender ◽  
Filtering Approach

Product review sites are widespread on the Internet and are rapidly gaining in popularity among consumers. This already large volume of user-generated content is dramatically growing every day, making it hard for consumers to filter out the worthwhile information which appears on the various review sites. There commendation system plays a significant role in solving the problem of information overload. This study proposes a framework which integrates a collaborative filtering approach and an opinion mining technique for movie recommendation. Within the proposed framework, sentiment analysis is first applied to the users’ reviews to detect consumer opinions about the movie they have watched and to explore the individual’s preference profile. Traditional recommendation models are overly dependent on preference ratings and often suffer from the problem of ‘data sparsity’. Experimental results obtained from real online reviews show that our proposed method is effective in dealing with insufficient data and is more accurate and efficient than existing traditional methods.

Opinion mining technique for developing student feedback analysis system using lexicon-based approach (OMFeedback)

2019 ◽  
Vol 25 (4) ◽  
pp. 2549-2560 ◽  
Author(s):  
Muslihah Wook ◽  
Noor Afiza Mat Razali ◽  
Suzaimah Ramli ◽  
Norshahriah Abdul Wahab ◽  
Nor Asiakin Hasbullah ◽  
...  
Keyword(s):  
Opinion Mining ◽  
Student Feedback ◽  
Feedback Analysis ◽  
Mining Technique ◽  
Analysis System

scholarly journals Opinion mining on newspaper headlines using SVM and NLP

2019 ◽  
Vol 9 (3) ◽  
pp. 2152 ◽  
Author(s):  
Chaudhary Jashubhai Rameshbhai ◽  
Joy Paulose
Keyword(s):  
Support Vector Machine ◽  
Natural Language Processing ◽  
Language Processing ◽  
Opinion Mining ◽  
Confusion Matrix ◽  
Support Vector ◽  
Text Data ◽  
Mining Technique ◽  
Svm Model ◽  
Linear Svm

<p>Opinion Mining also known as Sentiment Analysis, is a technique or procedure which uses Natural Language processing (NLP) to classify the outcome from text. There are various NLP tools available which are used for processing text data. Multiple research have been done in opinion mining for online blogs, Twitter, Facebook etc. This paper proposes a new opinion mining technique using Support Vector Machine (SVM) and NLP tools on newspaper headlines. Relative words are generated using Stanford CoreNLP, which is passed to SVM using count vectorizer. On comparing three models using confusion matrix, results indicate that Tf-idf and Linear SVM provides better accuracy for smaller dataset. While for larger dataset, SGD and linear SVM model outperform other models.</p>

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