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Research Paper | Computer Science & Engineering | Kazakhstan | Volume 13 Issue 11, November 2024 | Popularity: 5.5 / 10
Enhancing Recommendation Systems with Fuzzy Logic-Based Collaborative Filtering
Yernar Seitay
Abstract: This research addresses the challenges of sparsity and uncertainty in user-product interaction data by integrating fuzzy logic with collaborative filtering. The proposed fuzzy CF framework utilizes cosine similarity metrics and triangular membership functions to refine similarity scores and predict ratings for unrated items. Experimental results demonstrate that while the fuzzy CF system slightly increases RMSE, it significantly enhances recommendation coverage, making it robust in sparse data scenarios. The findings suggest that fuzzy logic effectively complements traditional CF methods to improve recommendation quality and coverage.
Keywords: collaborative filtering, recommendation system, user-product interaction, fuzzy inference system, sparse data handling
Edition: Volume 13 Issue 11, November 2024
Pages: 1485 - 1488
DOI: https://www.doi.org/10.21275/SR241124204713
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