By Topic

Recommender system based on data mining: Interlibrary case study

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ammar Jalalimanesh ; Information Engineering Department, Iranian Research Institute for Information Science and Technology, Iran ; Masoud Mansoury ; Hadi Gandomi

This paper introduces architecture for recommender system in domain of interlibrary services. The system works based on rules that was extracted from historical usage logs by the aid of data mining techniques. The paper also describes experimental results of pilot implementation of system for Ghadir project (resource sharing program in Iran). The pilot design and implementation phases were data gathering, pre-processing and warehousing, data mining and association rules extraction that all were described in the paper. The logs of 10 years usage of Ghadir project were processed and stored in data warehouse. Then CLOPE algorithm was applied on data to cluster users. After that decision tree technique was used for rule extraction.

Published in:

20th Iranian Conference on Electrical Engineering (ICEE2012)

Date of Conference:

15-17 May 2012