research-article

RecDB: towards DBMS support for online recommender systems

Author:

Mohamed SarwatAuthors Info & Claims

PhD '12: Proceedings of the on SIGMOD/PODS 2012 PhD Symposium

Pages 33 - 38

https://doi.org/10.1145/2213598.2213608

Published: 20 May 2012 Publication History

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.

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Cited By

Sarwat MBao JEldawy ALevandoski JMagdy AMokbel MGhinita GNeville JNewsam S(2012)The anatomy of SindbadProceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks10.1145/2442796.2442798(1-4)Online publication date: 6-Nov-2012
https://dl.acm.org/doi/10.1145/2442796.2442798

Index Terms

RecDB: towards DBMS support for online recommender systems

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Recommender systems have been developed to address the abundance of choice we face in taste domains (films, music, restaurants) when shopping or going out. However, consumers currently struggle to evaluate the appropriateness of recommendations offered. ...
Double-sided recommendations: a novel framework for recommender systems
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Recommender systems actively provide users with suggestions of potentially relevant items. In this paper we introduce double-sided recommendations, i.e., recommendations consisting of an item and a group of people with whom such an item could be ...

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Published In

cover image ACM Conferences

PhD '12: Proceedings of the on SIGMOD/PODS 2012 PhD Symposium

May 2012

80 pages

ISBN:9781450313261

DOI:10.1145/2213598

General Chairs:
Xin Luna Dong
AT&T Labs-Research, USA
,
M. Tamer Özsu
University of Waterloo, Canada

Copyright © 2012 ACM.

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 May 2012

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SIGMOD/PODS '12

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SIGMOD

SIGMOD/PODS '12: International Conference on Management of Data

May 20, 2012

Arizona, Scottsdale, USA

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Overall Acceptance Rate 8 of 14 submissions, 57%

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Cited By

Sarwat MBao JEldawy ALevandoski JMagdy AMokbel MGhinita GNeville JNewsam S(2012)The anatomy of SindbadProceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks10.1145/2442796.2442798(1-4)Online publication date: 6-Nov-2012
https://dl.acm.org/doi/10.1145/2442796.2442798

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