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Session-Based Recommendations

7개 벤치마크 · 논문 173편 · 이 태스크의 논문 보기 →

Benchmarks

Diginetica

결과 13개

yoochoose1/64

결과 11개

yoochoose1

결과 4개

yoochoose1/4

결과 4개

Last.FM

결과 3개

Retailrocket

결과 2개

Gowalla

결과 1개

Most implemented

Papers

SemSR: Semantics aware robust Session-based Recommendations

2025-08-28 · Jyoti Narwariya, Priyanka Gupta, Muskan Gupta, Jyotsana Khatri 외 arxiv

Session-based recommendation (SR) models aim to recommend items to anonymous users based on their behavior during the current session. While various SR models in the literature utilize item sequences to predict the next …

Session-Based Recommendations

Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation

2025-07-07 · Jinpeng Chen, Jianxiang He, Huan Li, Senzhang Wang 외

Session-based Recommendation (SBR) aims to predict the next item a user will likely engage with, using their interaction sequence within an anonymous session. Existing SBR models often focus only on single-session inform…

Contrastive LearningDenoisingSession-Based Recommendations

Rethinking Contrastive Learning in Session-based Recommendation

2025-06-05 · Xiaokun Zhang, Bo Xu, Fenglong Ma, Zhizheng Wang 외

Session-based recommendation aims to predict intents of anonymous users based on limited behaviors. With the ability in alleviating data sparsity, contrastive learning is prevailing in the task. However, we spot that exi…

Contrastive LearningSelf-Supervised LearningSession-Based Recommendations

A Survey on Side Information-driven Session-based Recommendation: From a Data-centric Perspective

2025-05-18 · Xiaokun Zhang, Bo Xu, Chenliang Li, Bowei He 외

Session-based recommendation is gaining increasing attention due to its practical value in predicting the intents of anonymous users based on limited behaviors. Emerging efforts incorporate various side information to al…

Session-Based RecommendationsSurvey

Linear Item-Item Model with Neural Knowledge for Session-based Recommendation

2025-04-21 · Minjin Choi, Sunkyung Lee, Seongmin Park, Jongwuk Lee

Session-based recommendation (SBR) aims to predict users' subsequent actions by modeling short-term interactions within sessions. Existing neural models primarily focus on capturing complex dependencies for sequential it…

Session-Based Recommendations

Distilling Transitional Pattern to Large Language Models for Multimodal Session-based Recommendation

2025-04-13 · Jiajie Su, Qiyong Zhong, Yunshan Ma, Weiming Liu 외

Session-based recommendation (SBR) predicts the next item based on anonymous sessions. Traditional SBR explores user intents based on ID collaborations or auxiliary content. To further alleviate data sparsity and cold-st…

Mutual Information EstimationSession-Based Recommendations

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