Cross-domain sequential recommendation

Results 1 to 10 of about 33 (31)

Exploiting high-order behaviour patterns for cross-domain sequential recommendation

Connection Science, 2022
The cross-domain sequential recommendation aims to predict the next item based on a sequence of recorded user behaviours in multiple domains. We propose a novel Cross-domain Sequential Recommendation approach with Graph-Collaborative Filtering (CsrGCF ...
Bingyuan Wang +6 more
doaj +2 more sources

CD-SPM: Cross-domain book recommendation using sequential pattern mining and rule mining

Journal of King Saud University: Computer and Information Sciences, 2022
Recommender system suggests a personalized recommendation by filtering the information based on users interest. Nowadays, users like to purchase the best possible items and services to spend the shortest span of time.
Taushif Anwar, V. Uma
doaj +3 more sources

Robust Cross-Domain Sequential Recommendation Driven by Causal Disentanglement and Counterfactual Generation

IEEE Access
Sequential recommendation systems are confronted with the dual challenges of data sparsity and domain bias. Especially in cross-domain scenarios, user interests are deeply coupled with domain-specific noise, which severely restricts recommendation ...
Jianhua Zhao, Ning Liu, Ronghua Zhao
doaj +1 more source

Large Language Model Semantic-Guided Counterfactual Data Augmentation for Cross-Domain Sequential Recommendation

IEEE Access
Cross-domain sequential recommendation leverages source-domain interactions to alleviate target-domain sparsity, yet existing methods struggle with semantic gaps, insufficient training signals under extreme sparsity, and negative transfer caused by user ...
Ning Liu, Jianhua Zhao, Ronghua Zhao
doaj +1 more source

Contrastive cross-domain sequential recommendation with attention-aware mechanism

Complex & Intelligent Systems
Cross-domain sequential recommendation (CDSR) aims to predict future sequential interactions in a target domain by analyzing historical sequence data from different domains.
Wei Zhao, Bo Li, Xian Mo
doaj +1 more source

An improved cross-domain sequential recommendation model based on intra-domain and inter-domain contrastive learning

Complex & Intelligent Systems
Cross-domain recommendation aims to integrate data from multiple domains and introduce information from source domains, thereby achieving good recommendations on the target domain.
Jianjun Ni +4 more
doaj +1 more source

BASG: A Behavior-Augmented Semantic Generalization Framework for Zero-Shot Cross-Domain Sequential Recommendation

Big Data and Cognitive Computing
Training sequential recommenders for interaction-disjoint target domains is challenging: no target interaction data are available for training, model selection, or calibration.
Zihao Pan, Peilun Li, Yue Li
doaj +1 more source

Channel-Enhanced Contrastive Cross-Domain Sequential Recommendation

Data Science and Engineering
Sequential recommendation help users find interesting items by modeling the dynamic user-item interaction sequences. Due to the data sparseness problem, cross-domain sequential recommendation (CDSR) are proposed.
Liu Yufang +4 more
doaj +1 more source

Time-Aware Sequence Modeling of Student Activities: Calibrated Next-Event Prediction from Large-Scale Campus Logs

Technologies
Learning analytics increasingly relies on large-scale educational activity logs to understand student behavior and support intelligent decision making.
Khaled Abdalgader +3 more
doaj +1 more source

GUIDE: Generative User Intent Dual-Encoder for tourism recommendation

Egyptian Informatics Journal
Tourism and point-of-interest (POI) recommendation is inherently intent-dependent and context-sensitive, yet many existing methods primarily rely on user–item interactions or short-term behavioral sequences, making it difficult to capture the rich ...
Yonghua Yi +4 more
doaj +1 more source

contrastive learning
cross-domain recommendation
large language models