Nov 29, 2016 · In this paper, we develop a new model to tackle the CF problem which predicts user's ratings on previously unrated items by effectively ...
In this paper, we develop a new model to tackle the CF problem which predicts user's ratings on previously unrated items by effectively exploiting interactions ...
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In this paper, we develop a new model to tackle the CF problem which predicts user's ratings on previously unrated items by effectively exploiting interactions ...
We propose a new generative model to predict user's ratings on previously unrated items by considering review texts as well as hidden user communities and item ...
Bibliographic details on Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering.
Mar 26, 2021 · We propose a new generative model to predict user's ratings on previously unrated items by considering review texts as well as hidden user ...
Co-authors ; Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering. Y Xu, Q Yu, W Lam, T Lin.
We found that the social influence adaptively changes according to users' dynamic preferences. •. We developed a novel method SFRec to integrate static and ...
Traditional recommendation systems rely on users' explicit ratings or implicit interactions (e.g., likes, clicks, shares, saves) to learn user preferences and ...
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A review of task scheduling based ... Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering.