Index Link

  • RootNode
    • Co-operative College, Mandalay
    • Cooperative College, Phaunggyi
    • Co-operative University, Sagaing
    • Co-operative University, Thanlyin
    • Dagon University
    • Kyaukse University
    • Laquarware Technological college
    • Mandalay Technological University
    • Mandalay University of Distance Education
    • Mandalay University of Foreign Languages
    • Maubin University
    • Mawlamyine University
    • Meiktila University
    • Mohnyin University
    • Myanmar Institute of Information Technology
    • Myanmar Maritime University
    • National Management Degree College
    • Naypyitaw State Academy
    • Pathein University
    • Sagaing University
    • Sagaing University of Education
    • Taunggyi University
    • Technological University, Hmawbi
    • Technological University (Kyaukse)
    • Technological University Mandalay
    • University of Computer Studies, Mandalay
    • University of Computer Studies Maubin
    • University of Computer Studies, Meikhtila
    • University of Computer Studies Pathein
    • University of Computer Studies, Taungoo
    • University of Computer Studies, Yangon
    • University of Dental Medicine Mandalay
    • University of Dental Medicine, Yangon
    • University of Information Technology
    • University of Mandalay
    • University of Medicine 1
    • University of Medicine 2
    • University of Medicine Mandalay
    • University of Myitkyina
    • University of Public Health, Yangon
    • University of Veterinary Science
    • University of Yangon
    • West Yangon University
    • Yadanabon University
    • Yangon Technological University
    • Yangon University of Distance Education
    • Yangon University of Economics
    • Yangon University of Education
    • Yangon University of Foreign Languages
    • Yezin Agricultural University
    • New Index

Item

{"_buckets": {"deposit": "9a820bf5-fb14-4e75-9eb3-d0554616a642"}, "_deposit": {"created_by": 45, "id": "6326", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "recid", "value": "6326"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/6326", "sets": ["1605779935331", "user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Implementation of Recommender System Using Feature-Based Sentiment Analysis", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "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."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Collaborative Filtering (CF)"}, {"interim": "Data sparsity"}, {"interim": "Review text"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-11-20"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Implementation of Recommender System Using Feature-Based Sentiment Analysis.pdf", "filesize": [{"value": "1.4 Mb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensefree": "© 2018 ICAIT", "licensetype": "license_free", "mimetype": "application/pdf", "size": 1400000.0, "url": {"url": "https://meral.edu.mm/record/6326/files/Implementation of Recommender System Using Feature-Based Sentiment Analysis.pdf"}, "version_id": "f535d0d3-bcd6-4ee3-ab6b-c7c3c50e8cb1"}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "ICAIT-2018", "subitem_c_date": "1-2 November, 2018", "subitem_conference_title": "2nd International Conference on Advanced Information Technologies", "subitem_place": "Yangon, Myanmar", "subitem_session": "Natural Language Processing", "subitem_website": "https://www.uit.edu.mm/icait-2018/"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Nyein Ei Ei Kyaw"}, {"subitem_authors_fullname": "Thinn Thinn Wai"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Conference paper"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2018-11-02"}, "item_title": "Implementation of Recommender System Using Feature-Based Sentiment Analysis", "item_type_id": "21", "owner": "45", "path": ["1605779935331"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000006326", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-11-20"}, "publish_date": "2020-11-20", "publish_status": "0", "recid": "6326", "relation": {}, "relation_version_is_last": true, "title": ["Implementation of Recommender System Using Feature-Based Sentiment Analysis"], "weko_shared_id": -1}

Implementation of Recommender System Using Feature-Based Sentiment Analysis

http://hdl.handle.net/20.500.12678/0000006326
fa03e9ba-ad77-4956-bc43-aa8713602dc9
9a820bf5-fb14-4e75-9eb3-d0554616a642
None
Name / File License Actions
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/
0
0
views
downloads
Views Downloads

Export

OAI-PMH
  • OAI-PMH DublinCore
Other Formats