RECATHON: A Middleware for Context-Aware Recommendation in Database Systems

Mohamed Sarwat, James L. Avery, Mohamed F. Mokbel

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

3 Scopus citations

Abstract

This paper presents RECATHON, a context-aware recommender system built entirely inside a database system. Unlike traditional recommender systems that are context-free where they support the general query of Recommend movies for a certain user, RECATHON users can request recommendations based on their age, location, gender, or any other contextual/demographical/preferential user attribute. A main challenge of supporting such kind of recommenders is the difficulty of deciding what attributes to build recommenders on. RECATHON addresses this challenge as it supports building recommenders in database systems in an analogous way to building index structures. Users can decide to create recommenders on selected attributes, e.g., Age and/or gender, and then entertain efficient support of multidimensional recommenders on the selected attributes. RECATHON employs a multi-dimensional index structure for each built recommender that can be accessed using novel query execution algorithms to support efficient retrieval for recommender queries. Experimental results based on an actual prototype of RECATHON, built inside Postgre SQL, using real Movie Lens and Foursquare data show that RECATHON exhibits real time performance for large-scale multidimensional recommendation.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 16th International Conference on Mobile Data Management, MDM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages54-63
Number of pages10
ISBN (Electronic)9781479999729
DOIs
StatePublished - Sep 11 2015
Event16th IEEE International Conference on Mobile Data Management, MDM 2015 - Pittsburgh, United States
Duration: Jun 15 2015Jun 18 2015

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
Volume1
ISSN (Print)1551-6245

Other

Other16th IEEE International Conference on Mobile Data Management, MDM 2015
CountryUnited States
CityPittsburgh
Period6/15/156/18/15

Keywords

  • Context
  • Database
  • Recommender

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    Sarwat, M., Avery, J. L., & Mokbel, M. F. (2015). RECATHON: A Middleware for Context-Aware Recommendation in Database Systems. In Proceedings - 2015 IEEE 16th International Conference on Mobile Data Management, MDM 2015 (pp. 54-63). [7264304] (Proceedings - IEEE International Conference on Mobile Data Management; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MDM.2015.63