{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/hypergraphs-with-attention-on-reviews-for","title":"Hypergraphs with Attention on Reviews for Explainable Recommendation","arxiv_id":null,"date":"2024-03-20","proceeding":"European Conference on Information Retrieval 2024 3","authors":["Theis E. Jendal","Trung-Hoang Le","Hady W. Lauw","Matteo Lissandrini","Peter Dolog and Katja Hose"],"abstract":"Given a recommender system based on reviews, the chal-lenges are how to effectively represent the review data and how to explainthe produced recommendations. We propose a novel review-specific Hy-pergraph (HG) model, and further introduce a model-agnostic explaina-bility module. The HG model captures high-order connections betweenusers, items, aspects, and opinions while maintaining information aboutthe review. The explainability module can use the HG model to ex-plain a prediction generated by any model. We propose a path-restrictedreview-selection method biased by the user preference for item reviewsand propose a novel explanation method based on a review graph. Ex-periments on real-world datasets confirm the ability of the HG model tocapture appropriate explanations.","url_abs":"https://link.springer.com/chapter/10.1007/978-3-031-56027-9_14","url_pdf":"https://www.dropbox.com/scl/fi/mqg5cyztb2dy04c2eg6ua/ecir24.pdf?rlkey=qvj08y33hfvasl6syolp1yxg1&e=1&dl=0","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"hypergraphs-with-attention-on-reviews-for","repo_url":"https://github.com/PreferredAI/Hypar","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"hypergraphs-with-attention-on-reviews-for","repo_url":"https://github.com/PreferredAI/cornac","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"explainable-recommendation","task_name":"Explainable Recommendation"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}