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However, social network information contains noise, which can be detrimental to recommendation performance. Current social recommendation models are deficient in feature validation and extraction of social data. To fill that gap, we propose a novel model called Social View Explorer Collaborative Filtering (SVE-CF) which aims to extract significant consistent signals from the noisy social network. First, SVE-CF correlates users\u2019 social and interaction behaviors, creating follow, joint, and interaction views to represent all interaction patterns. Second, it samples unlabeled examples from users to assess consistency across the three views, assigning pseudo-labels as evidence of social homophily. Third, it selects top-k pseudo-labels to amplify significant consistent signals and minimize noise through tri-view joint learning. Extensive experiments are conducted to demonstrate the effectiveness of the proposed model over the commonly used state-of-the-art (SOTA) methods.<\/jats:p>","DOI":"10.1007\/s10844-024-00865-w","type":"journal-article","created":{"date-parts":[[2024,6,26]],"date-time":"2024-06-26T06:06:56Z","timestamp":1719382016000},"page":"1703-1724","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Improving graph collaborative filtering with view explorer for social recommendation"],"prefix":"10.1007","volume":"62","author":[{"given":"Yongrui","family":"Duan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yijun","family":"Tu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yusheng","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofeng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,26]]},"reference":[{"key":"865_CR1","doi-asserted-by":"publisher","unstructured":"Bruna, J., Zaremba, W. & Szlam, A., et\u00a0al. 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