Improved user similarity computation for finding friends in your location View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Georgios Tsakalakis, Polychronis Koutsakis

ABSTRACT

Recommender systems are most often used to predict possible ratings that a user would assign to items, in order to find and propose items of possible interest to each user. In our work, we are interested in a system that will analyze user preferences in order to find and connect people with common interests that happen to be in the same geographical area, i.e., a “friend” recommendation system. We present and propose an algorithm, Egosimilar+, which is shown to achieve superior performance against a number of well-known similarity computation methods from the literature. The algorithm adapts ideas and techniques from the recommender systems literature and the skyline queries literature and combines them with our own ideas on the importance and utilization of item popularity. More... »

PAGES

36

References to SciGraph publications

  • 2018-12. Personality classification based on profiles of social networks’ users and the five-factor model of personality in HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
  • 2012-09. An analysis of peer similarity for recommendations in P2P systems in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2017-12. Trust reality-mining: evidencing the role of friendship for trust diffusion in HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
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    http://scigraph.springernature.com/pub.10.1186/s13673-018-0160-7

    DOI

    http://dx.doi.org/10.1186/s13673-018-0160-7

    DIMENSIONS

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