Distributed Recommender Profiling and Selection with Gittins Indices

Weng, Li-Tung S., Xu, Yue, Li, Yuefeng, & Nayak, Richi (2006) Distributed Recommender Profiling and Selection with Gittins Indices. In Cheung, K.W. (Ed.) IEEE/WIC/ACM International Conference on Web Intelligence, 2006. WI 2006, 18-22 December 2006, Hong Kong, China.

View at publisher


Most existing recommender systems nowadays operate in a single organizational base, and very often they do not have sufficient resources to be used in order to generate quality recommendations. Therefore, it would be beneficial if recommender systems of different organizations can cooperate together to share their resources and recommendations. In this paper, we present a distributed recommender system model that consists of multiple recommender systems from different organizations. With the hope to provide better recommendation service to users, the recommender systems can improve their performances by sharing their recommendations cooperatively. A recommender selection technique based on the Gittins indices is presented in this paper, and it makes selections based on the stability, average performance and selection frequency of the recommenders.

Impact and interest:

0 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

215 since deposited on 05 Sep 2007
16 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 9350
Item Type: Conference Paper
Refereed: No
Keywords: information filtering, information filters
DOI: 10.1109/WI.2006.62
ISBN: 0769527477
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2006 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 05 Sep 2007 00:00
Last Modified: 29 Feb 2012 13:25

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page