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This method is based on fuzzy subjective trust model and measures the trust value of users in social networks correctly by constructing the set of trusted users. Combined with the improved traditional collaborative filtering recommendation algorithm, the target user recommendation is finally formed.
In order to resist malicious attacks and improve recommendation accuracy, this paper proposes a collaborative filtering recommendation algorithm based on fuzzy ...
PDF | In order to resist malicious attacks and improve recommendation accuracy, this paper proposes a collaborative filtering recommendation algorithm.
Oct 22, 2024 · This study proposes a novel collaborative filtering framework which integrates both subjective and objective information to generate ...
Aug 15, 2024 · An extended trust and distrust network-based dual fuzzy recommendation model (ETD-DFR) is proposed. First, the trust and distrust network is constructed.
The proposed algorithm has greatly improved the recommendation accuracy. Key words: Collaborative Filtering; Fuzzy Clustering Algorithm; Recommended model.
Collaborative filtering is a method of analyzing user behavior and identifying patterns of common interests to make personalized recommendations.
Mar 24, 2023 · A recommendation method based on heterogeneous information networks and multiple trust relationships is proposed.
Nov 29, 2023 · A project studying algorithmic amplification and distortion, and exploring ways to minimize harmful amplifying or distorting effects.
Oct 19, 2022 · This article presents a recommender predictive model based on collaborative filtering techniques that incorporate a fuzzy-driven quantifier, ...
Missing: subjective | Show results with:subjective