RecDB: Towards DBMS support for online recommender systems

Mohamed Sarwat, Mohamed F. Mokbel

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

3 Scopus citations

Abstract

Recommender systems have become popular in both commercial and academic settings. The main purpose of recommender systems is to suggest to users useful and interesting items or content (data) from a considerably large set of items. Traditional recommender systems do not take into account system issues (i.e., scalability and query efficiency). In an age of staggering web use growth and everpopular social media applications (e.g., Facebook, Google Reader), users are expressing their opinions over a diverse set of data (e.g., news stories, Facebook posts, retail purchases) faster than ever. In this paper, we propose RecDB; a fully fledged database system that provides online recommendation to users. We implement RecDB using existing open source database system Apache Derby, and we use showcase the effectiveness of RecDB by adopting inside Sindbad; a Location-Based Social Networking system developed at University of Minnesota.

Original languageEnglish (US)
Title of host publicationSIGMOD/PODS '12 PhD Symposium - Proceedings of the SIGMOD/PODS 2012 PhD Symposium
Pages33-37
Number of pages5
DOIs
StatePublished - Jun 26 2012
Externally publishedYes
EventSIGMOD/PODS '12 PhD Symposium - Scottsdale, AZ, United States
Duration: May 20 2012May 20 2012

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

ConferenceSIGMOD/PODS '12 PhD Symposium
CountryUnited States
CityScottsdale, AZ
Period5/20/125/20/12

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Keywords

  • filtered recommendation
  • model maintenance
  • query processing
  • recommender systems
  • social networking

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Sarwat, M., & Mokbel, M. F. (2012). RecDB: Towards DBMS support for online recommender systems. In SIGMOD/PODS '12 PhD Symposium - Proceedings of the SIGMOD/PODS 2012 PhD Symposium (pp. 33-37). (Proceedings of the ACM SIGMOD International Conference on Management of Data). https://doi.org/10.1145/2213598.2213608