{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T22:44:43Z","timestamp":1773355483227,"version":"3.50.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>Session-based recommendation is a challenging problem due to the inherent uncertainty of user behavior and the limited historical click information. Latent factors and the complex dependencies within the user\u2019s current session have an important impact on the user's main intention, but the existing methods do not explicitly consider this point. In this paper, we propose a novel model, Interest Shift and Latent Factors Combination Model (ISLF), which can capture the user's main intention by taking into account the user\u2019s interest shift (i.e. long-term and short-term interest) and latent factors simultaneously. In addition, we experimentally give an explicit explanation of this combination in our ISLF. Our experimental results on three benchmark datasets show that our model achieves state-of-the-art performance on all test datasets.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/799","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:05Z","timestamp":1564299965000},"page":"5765-5771","source":"Crossref","is-referenced-by-count":47,"title":["ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation"],"prefix":"10.24963","author":[{"given":"Jing","family":"Song","sequence":"first","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, China"}]},{"given":"Hong","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, China"},{"name":"School of Computer Science, The University of Adelaide, Adelaide, Australia"}]},{"given":"Zijing","family":"Ou","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, China"}]},{"given":"Junyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, China"}]},{"given":"Teng","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, China"}]},{"given":"Shangsong","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Data and Computer Science, Sun Yat-sen University, China"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:51:54Z","timestamp":1564300314000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/799"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/799","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}