Towards inferring ratings from user behavior in BitTorrent communities

Róbert Ormándi, István Hegedus, Kornél Csernai, Márk Jelasity

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Peer-to-peer file-sharing has been increasingly popular in the last decade. In most cases file-sharing communities provide only minimal functionality, such as search and download. Extra features such as recommendation are difficult to implement because users are typically unwilling to provide sufficient rating information for the items they download. For this reason, it would be desirable to utilize user behavior to infer implicit ratings. For example, if a user deletes a file after downloading it, we could infer that the rating is low, or if the user is seeding the file for a long time, the rating is high. In this paper we demonstrate that it is indeed possible to infer implicit ratings from user behavior. We work with a large trace of Filelist.org, a BitTorrent-based private community, and demonstrate that we can identify a binary like/dislike distinction over the set of files users are downloading, using dynamic features of swarm membership. The resulting database containing the inferred ratings will be published online publicly and it can be used as a benchmark for P2P recommender systems.

Original languageEnglish
Title of host publication19th IEEE International Workshops on Enabling Technologies
Subtitle of host publicationInfrastructure for Collaborative Enterprises, WETICE 2010
Pages217-222
Number of pages6
DOIs
Publication statusPublished - Aug 27 2010
Event19th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2010 - Larissa, Greece
Duration: Jun 28 2010Jun 30 2010

Publication series

NameProceedings of the Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE
ISSN (Print)1524-4547

Other

Other19th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2010
CountryGreece
CityLarissa
Period6/28/106/30/10

Keywords

  • Database
  • Peer-to-peer
  • Recommendation

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture

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  • Cite this

    Ormándi, R., Hegedus, I., Csernai, K., & Jelasity, M. (2010). Towards inferring ratings from user behavior in BitTorrent communities. In 19th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2010 (pp. 217-222). [5541777] (Proceedings of the Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE). https://doi.org/10.1109/WETICE.2010.41