Abstract
AbstractRecommender systems are widely adopted as an increasing research and development area, since they provide users with diverse and useful information tailored to their needs. Several strategies have been proposed, and in most of them some concept of similarity is used as a core part of the approach, either between items or between users. At the same time, Siamese Neural Networks are being used to capture the similarity of items in the image domain, as they are defined as a subtype of Artificial Neural Networks built with (at least two) identical networks that share their weights. In this review, we study the proposals done in the intersection of these two fields, that is, how Siamese Networks are being used for recommendation. We propose a classification that considers different recommendation problems and algorithmic approaches. Some research directions are pointed out to encourage future research. To the best of our knowledge, this paper is the first comprehensive survey that focuses on the usage of Siamese Neural Networks for Recommender Systems.
Funder
Ministerio de Ciencia e Innovación
Universidad Autónoma de Madrid
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Cited by
2 articles.
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2. Recommender System using Audio and Lyrics;2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC);2023-07-06