SDM最新文献

筛选

英文中文

Denoising Long- and Short-term Interests for Sequential Recommendation 为序列推荐对长期和短期兴趣去噪

SDM Pub Date : 2024-07-20 DOI: 10.1137/1.9781611978032.63

Xinyu Zhang, Beibei Li, Beihong Jin

{"title":"Denoising Long- and Short-term Interests for Sequential Recommendation","authors":"Xinyu Zhang, Beibei Li, Beihong Jin","doi":"10.1137/1.9781611978032.63","DOIUrl":"https://doi.org/10.1137/1.9781611978032.63","url":null,"abstract":"User interests can be viewed over different time scales, mainly including stable long-term preferences and changing short-term intentions, and their combination facilitates the comprehensive sequential recommendation. However, existing work that focuses on different time scales of user modeling has ignored the negative effects of different time-scale noise, which hinders capturing actual user interests and cannot be resolved by conventional sequential denoising methods. In this paper, we propose a Long- and Short-term Interest Denoising Network (LSIDN), which employs different encoders and tailored denoising strategies to extract long- and short-term interests, respectively, achieving both comprehensive and robust user modeling. Specifically, we employ a session-level interest extraction and evolution strategy to avoid introducing inter-session behavioral noise into long-term interest modeling; we also adopt contrastive learning equipped with a homogeneous exchanging augmentation to alleviate the impact of unintentional behavioral noise on short-term interest modeling. Results of experiments on two public datasets show that LSIDN consistently outperforms state-of-the-art models and achieves significant robustness.","PeriodicalId":508514,"journal":{"name":"SDM","volume":"25 5","pages":"544-552"},"PeriodicalIF":0.0,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141819368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extension of the Dip-test Repertoire - Efficient and Differentiable p-value Calculation for Clustering 扩展《浸渍测试曲目》--高效、可区分的聚类 p 值计算

SDM Pub Date : 2023-12-19 DOI: 10.1137/1.9781611977653.ch13

L. G. M. Bauer, Collin Leiber, Christian Böhm, Claudia Plant

引用次数: 0