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Improving session-based recommendation adopting linear regression based re-ranking

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

Due to the increase in the importance of giving real-time recommendation to e-commerce users, session-based recommender systems become more popular. Session-based recommendation systems have the ability to adapt quickly to respond to changes in user interests and newly added items. The ranking is the core part of recommender systems regardless of recommender system type. Re-ranking is applied to recommender systems to have more personalised recommendations by considering context-awareness. In this paper, we proposed an approach to re-rank recommended items by using a linear regression model. In our approach, we use users' current session features and temporal features of recommended items to measure a user's interest level on a recommended item. We focus on having better recall and precision scores with fewer recommendations to able to prove the success of our re-ranking strategy. We conduct computational experiments on six real-world datasets and show that after applying re-ranking, we can get higher recall and precision scores. These results confirm that taking user interest level on an item in a session into account can improve the chance of getting correct items in top 5 recommendations.
Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks (IJCNN) 2020
PublisherInstitute of Electrical and Electronics Engineers
Publication statusAccepted for publication - 17 May 2020
EventIEEE World Congress on Computational Intelligence (WCCI) 2020 - Glasgow, United Kingdom
Duration: 19 Jul 202024 Jul 2020

Publication series

Name2020 International Joint Conference on Neural Networks (IJCNN)
PublisherIEEE
ISSN (Print)2161-4393
ISSN (Electronic)2161-4407

Conference

ConferenceIEEE World Congress on Computational Intelligence (WCCI) 2020
CountryUnited Kingdom
CityGlasgow
Period19/07/2024/07/20

Documents

  • multiwayranking

    Rights statement: The embargo end date of 2050 is a temporary measure until we know the publication date. Once we know the publication date the full text of this article will be able to view shortly afterwards.

    Accepted author manuscript (Post-print), 230 KB, PDF document

    Due to publisher’s copyright restrictions, this document is not freely available to download from this website until: 1/01/50

Related information

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ID: 20955148