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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 36/2023

16.06.2023 | S.I.: Evolutionary Computation based Methods and Applications for Data Processing

A graph-based collaborative filtering algorithm combining implicit user preference and explicit time-related feedback

verfasst von: G. Suganeshwari, Syed Ibrahim Syed Ibrahim Peer Mohamed, Vijayan Sugumaran

Erschienen in: Neural Computing and Applications | Ausgabe 36/2023

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Abstract

Collaborative filtering is one of the most extensively utilized recommendation algorithms in the e-commerce industry. It typically relies either on implicit or explicit feedback. The existing collaborative approaches fail to capture changes in user preferences while integrating implicit and explicit data. To model the user's current preference, we propose a novel graph-based CWALK algorithm that combines time-related item correlation explicitly and the user's preference for an item implicitly. In the first stage, we cluster users based on their rating behavior, and in the second stage, we combine implicit and explicit feedback to construct a matrix for each user group. A random-walk-with-restart is employed on the matrix to generate a recommendation for each user. Extensive evaluation using the real-world MovieLens dataset shows that the proposed method improves the accuracy of recommendations.
Vorheriger Artikel Performance analysis of the asymmetric dual-queue periodic query threshold service polling system
Nächster Artikel Logistic regression prediction models and key influencing factors analysis of diabetes based on algorithm design

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Metadaten
Titel
A graph-based collaborative filtering algorithm combining implicit user preference and explicit time-related feedback
verfasst von
G. Suganeshwari
Syed Ibrahim Syed Ibrahim Peer Mohamed
Vijayan Sugumaran
Publikationsdatum
16.06.2023
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 36/2023
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-023-08694-8

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