A Recommender System With IBA Similarity Measure

Nevena Vranić (), Pavle Milošević (), Ana Poledica () and Bratislav Petrović ()
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Nevena Vranić: University of Belgrade
Pavle Milošević: University of Belgrade
Ana Poledica: University of Belgrade
Bratislav Petrović: University of Belgrade

A chapter in Advances in Operational Research in the Balkans, 2020, pp 275-290 from Springer

Abstract: Abstract Recommender systemsRecommender System (RS) help users to reduce the amount of time they spend to find the items they are interested in. One of the most successful approaches is collaborative filteringCollaborative Filtering (CF). The main feature of a recommender system is its ability to predict user’s interests by analyzing the behavior of this particular user and/or the behavior of other similar users to generate personalized recommendations. Identification of neighbor users who have had similar taste to the target user in the past is a crucial process for successful application of collaborative filteringCollaborative Filtering (CF). In this paper, we proposed a collaborative filtering method that uses interpolative Boolean algebraInterpolative Boolean Algebra (IBA) for calculation of similarity between users. In order to analyze the effectiveness of the proposed approach we used three common datasets: MovieLens 100K, MovieLens 1M, and CiaoDVD. We compared a collaborative filteringCollaborative Filtering (CF) based on IBA similarity measureIBA similarity measure with two standard similarity measures: Pearson correlation and cosine-based coefficient. Even though statistical measures are traditionally used in recommender systems, proposed logic-based approach showed promising results on the tested datasets. A recommender system with IBA similarity measureIBA similarity measure outperformed the others in most cases.

Keywords: Recommender systems; Collaborative filtering; User-based collaborative filtering; Interpolative boolean algebra; Similarity modeling; IBA similarity measure (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-21990-1_17

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DOI: 10.1007/978-3-030-21990-1_17

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