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Fair-SRS: A Fair Session-based Recommendation System

Published: 15 February 2022 Publication History

Abstract

This paper demonstrates Fair-SRS, a Fair Session-based Recommendation System that predicts user's next click based on their historical and current sessions. Fair-SRS provides personalized and diversified recommendations in two main steps: (1) forming user's session graph embeddings based on their long- and short-term interests, and (2) computing user's level of interest in diversity based on their recently-clicked items' similarity. In real-world scenarios, users tend to interact with more or fewer contents at different times, and providers expect to receive more exposure for their items. To achieve the objectives of both sides, the proposed Fair-SRS optimizes recommendations by making a trade-off between accuracy and personalized diversity.

Supplementary Material

MP4 File (WSDM22-de013.mp4)
In this presentation, I am going to talk about our demo paper titled as ''Fair-SRS: A Fair Session-based Recommendation System''. I first give a brief introduction about recommender systems, session-based recommender systems, different characteristics of session-based recommender systems over traditional recommenders, the main framework of the proposed method, experimental results and then a display of our public demo dashboard. We build a demo dashboard of Fair-SRS4 on the sub-sample of Xing data using Streamlit. This dashboard demonstrates Fair-SRS in three pages: (1) About Fair-SRS, (2) Top-k recommendations, and (3) Item Network. In the first page, we explain the main framework of the proposed Fair-SRS model with a toy example. In the second page, all steps for generating top-k recommendations are shown. Finally, in the third page, the item network is visualized. It can be zoomed in and out so that people can click on nodes and see their connected items.

References

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Cited By

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  • (2025)Session-Oriented Fairness-Aware Recommendation via Dual Temporal Convolutional NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.350945437:2(923-935)Online publication date: Feb-2025
  • (2024)Diversifying Sequential Recommendation with Retrospective and Prospective TransformersACM Transactions on Information Systems10.1145/365301642:5(1-37)Online publication date: 29-Apr-2024
  • (2024)Contrastive Learning on Medical Intents for Sequential Prescription RecommendationProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679836(748-757)Online publication date: 21-Oct-2024
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cover image ACM Conferences
WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
February 2022
1690 pages
ISBN:9781450391320
DOI:10.1145/3488560
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 15 February 2022

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Author Tags

  1. fairness
  2. personalized diversity
  3. session-based recommendation

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WSDM '22

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View all
  • (2025)Session-Oriented Fairness-Aware Recommendation via Dual Temporal Convolutional NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.350945437:2(923-935)Online publication date: Feb-2025
  • (2024)Diversifying Sequential Recommendation with Retrospective and Prospective TransformersACM Transactions on Information Systems10.1145/365301642:5(1-37)Online publication date: 29-Apr-2024
  • (2024)Contrastive Learning on Medical Intents for Sequential Prescription RecommendationProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679836(748-757)Online publication date: 21-Oct-2024
  • (2024)Heterogeneous Hypergraph Embedding for Node Classification in Dynamic NetworksIEEE Transactions on Artificial Intelligence10.1109/TAI.2024.34506585:11(5465-5477)Online publication date: Nov-2024
  • (2024)A long-tail alleviation post-processing framework based on personalized diversity of session recommendationExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123769249:PCOnline publication date: 17-Jul-2024
  • (2023)Incorporating user rating credibility in recommender systemsFuture Generation Computer Systems10.1016/j.future.2023.04.029147:C(30-43)Online publication date: 1-Oct-2023
  • (2023)Tag2Seq: Enhancing Session-Based Recommender Systems with Tag-Based LSTMInformation Integration and Web Intelligence10.1007/978-3-031-48316-5_37(398-407)Online publication date: 4-Dec-2023
  • (2022)PD-SRS: Personalized Diversity for a Fair Session-Based Recommendation SystemService-Oriented Computing10.1007/978-3-031-20984-0_23(331-339)Online publication date: 22-Nov-2022
  • (undefined)Incorporating User Rating Credibility in Recommender SystemsSSRN Electronic Journal10.2139/ssrn.4165425

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