Sentiment-Based Model for Recommender Systems

Nurul Aida Osman, Shahrul Azman Mohd Noah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recommender systems have proven to be a valuable way for online users to cope with the issues of information overload. They have become one of the most powerful and popular tools in electronic commerce as illustrated by Amazon.com, YouTube, Netflix, Yahoo, and IMDb. While recommender systems have shown significant contribution, they still suffer from the long-standing problems related to cold-start users and data-sparsity. This is due to the fact that recommendation algorithms mostly rely on users' rating to make prediction of items. Such ratings are usually insufficient and very limited. On the other hand, sentiment ratings of items which can be derived from online news services, blogs, social media or even from the recommender systems themselves are seen capable of providing better recommendations to user as opposed to tags alone. Sentiment-based model has been exploited in recommender systems to overcome the data-sparsity problem that exists in conventional recommender systems. Hence, embedding sentiment in recommender systems may significantly enhance the recommendation quality of recommender systems. Among the aims of this research is to integrate sentiment analysis in recommender systems particular to those items with no associated rating that commonly contribute to the problem of data-sparsity.

Original languageEnglish
Title of host publicationProceedings - 2018 4th International Conference on Information Retrieval and Knowledge Management
Subtitle of host publicationDiving into Data Sciences, CAMP 2018
EditorsShyamala Doraisamy, Azreen Azman, Dayang Nurfatimah Awg Iskandar, Muthukkaruppan Annamalai, Stefan Ruger, Fakhrul Hazman Yusoff, Nurazzah Abd. Rahman, Alistair Moffat, Shahrul Azman Mohd Noah
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages85-90
Number of pages6
ISBN (Print)9781538638125
DOIs
Publication statusPublished - 13 Sep 2018
Event4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018 - Kota Kinabalu, Sabah, Malaysia
Duration: 26 Mar 201828 Mar 2018

Other

Other4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018
CountryMalaysia
CityKota Kinabalu, Sabah
Period26/3/1828/3/18

Fingerprint

Recommender systems
rating
electronic commerce
Sentiment
Blogs
Electronic commerce
social media
weblog
news
Rating

Keywords

  • collaborative filtering
  • opinion mining
  • recommender systems
  • sentiment analysis

ASJC Scopus subject areas

  • Library and Information Sciences
  • Artificial Intelligence
  • Information Systems
  • Decision Sciences (miscellaneous)
  • Information Systems and Management

Cite this

Osman, N. A., & Mohd Noah, S. A. (2018). Sentiment-Based Model for Recommender Systems. In S. Doraisamy, A. Azman, D. N. A. Iskandar, M. Annamalai, S. Ruger, F. H. Yusoff, N. Abd. Rahman, A. Moffat, ... S. A. M. Noah (Eds.), Proceedings - 2018 4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018 (pp. 85-90). [8464694] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFRKM.2018.8464694

Sentiment-Based Model for Recommender Systems. / Osman, Nurul Aida; Mohd Noah, Shahrul Azman.

Proceedings - 2018 4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018. ed. / Shyamala Doraisamy; Azreen Azman; Dayang Nurfatimah Awg Iskandar; Muthukkaruppan Annamalai; Stefan Ruger; Fakhrul Hazman Yusoff; Nurazzah Abd. Rahman; Alistair Moffat; Shahrul Azman Mohd Noah. Institute of Electrical and Electronics Engineers Inc., 2018. p. 85-90 8464694.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Osman, NA & Mohd Noah, SA 2018, Sentiment-Based Model for Recommender Systems. in S Doraisamy, A Azman, DNA Iskandar, M Annamalai, S Ruger, FH Yusoff, N Abd. Rahman, A Moffat & SAM Noah (eds), Proceedings - 2018 4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018., 8464694, Institute of Electrical and Electronics Engineers Inc., pp. 85-90, 4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018, Kota Kinabalu, Sabah, Malaysia, 26/3/18. https://doi.org/10.1109/INFRKM.2018.8464694
Osman NA, Mohd Noah SA. Sentiment-Based Model for Recommender Systems. In Doraisamy S, Azman A, Iskandar DNA, Annamalai M, Ruger S, Yusoff FH, Abd. Rahman N, Moffat A, Noah SAM, editors, Proceedings - 2018 4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 85-90. 8464694 https://doi.org/10.1109/INFRKM.2018.8464694
Osman, Nurul Aida ; Mohd Noah, Shahrul Azman. / Sentiment-Based Model for Recommender Systems. Proceedings - 2018 4th International Conference on Information Retrieval and Knowledge Management: Diving into Data Sciences, CAMP 2018. editor / Shyamala Doraisamy ; Azreen Azman ; Dayang Nurfatimah Awg Iskandar ; Muthukkaruppan Annamalai ; Stefan Ruger ; Fakhrul Hazman Yusoff ; Nurazzah Abd. Rahman ; Alistair Moffat ; Shahrul Azman Mohd Noah. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 85-90
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