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  1. University of Information Technology
  2. International Conference on Advanced Information Technologies

Implementation of Recommender System Using Feature-Based Sentiment Analysis

http://hdl.handle.net/20.500.12678/0000006326
http://hdl.handle.net/20.500.12678/0000006326
fa03e9ba-ad77-4956-bc43-aa8713602dc9
9a820bf5-fb14-4e75-9eb3-d0554616a642
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Implementation Implementation of Recommender System Using Feature-Based Sentiment Analysis.pdf (1.4 Mb)
© 2018 ICAIT
Publication type
Conference paper
Upload type
Publication
Title
Title Implementation of Recommender System Using Feature-Based Sentiment Analysis
Language en
Publication date 2018-11-02
Authors
Nyein Ei Ei Kyaw
Thinn Thinn Wai
Description
A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management. Collaborative Filtering (CF)-based recommendation technique helps people to make choices based on the opinions of other people who share similar interests. This technique has been suffering from the problems of data sparsity and cold start because of insufficient user ratings or absence of data about users or items. This can affect the accuracy of the recommendation system. User-generated reviews are a plentiful source of user opinions and interests. The proposed personalized recommendation model uses feature base sentiment analysis using ontology that extracts the semantically related features to find the users’ individual preferences rather than rating scores in order to build user profiles that can be understood by user-based collaborative filtering recommendation model. The proposed model intends to alleviate data sparsity problem and to improve accuracy of recommender system by finding user preferences from review text.
Keywords
Collaborative Filtering (CF), Data sparsity, Review text
Conference papers
ICAIT-2018
1-2 November, 2018
2nd International Conference on Advanced Information Technologies
Yangon, Myanmar
Natural Language Processing
https://www.uit.edu.mm/icait-2018/
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