THE METHOD OF CONSTRUCTING RECOMMENDATIONS ONLINE ON THE TEMPORAL DYNAMICS OF USER INTERESTS USING MULTILAYER GRAPH

  • Serhii Chalyi Kharkiv National University of Radio Electronics, Ukraine
  • Inna Pribylnova Kharkiv National University of Radio Electronics, Ukraine
Keywords: recommender system, collaborative filtering, multi-layer graph, online recommendations, content personalization, area under the error curve

Abstract

The problem of the online construction of a rating list of objects in the recommender system is considered. A method for constructing recommendations online using the presentation of input data in the form of a multi-layer graph based on changes in user interests over time is proposed. The method is used for constructing recommendations in a situation with implicit feedback from the user. Input data are represented by a sequence of user choice records with a time stamp for each choice. The method includes the phases of pre-filtering of data and building recommendations by collaborative filtering of selected data. At pre-filtering of the input data, the subset of data is split into a sequence of fixed-length non-overlapping time intervals. Users with similar interests and records with objects of interest to these users are selected on a finite continuous subset of time intervals. In the second phase, the pre-filtered subset of data is used, which allows reducing the computational costs of generating recommendations. The method allows increasing the efficiency of building a rating list offered to the target user by taking into account changes in the interests of the user over time.

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Author Biographies

Serhii Chalyi, Kharkiv National University of Radio Electronics

Department of Information Control Systems

Inna Pribylnova, Kharkiv National University of Radio Electronics

Department of Information Control Systems

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Published
2019-05-31
How to Cite
Chalyi, S., & Pribylnova, I. (2019). THE METHOD OF CONSTRUCTING RECOMMENDATIONS ONLINE ON THE TEMPORAL DYNAMICS OF USER INTERESTS USING MULTILAYER GRAPH. EUREKA: Physics and Engineering, (3), 13-19. https://doi.org/10.21303/2461-4262.2019.00894
Section
Computer Science