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Fighting information overflow with personalized comprehensive information access: A proactive job recommender

Lee, DH and Brusilovsky, P (2007) Fighting information overflow with personalized comprehensive information access: A proactive job recommender. In: UNSPECIFIED UNSPECIFIED. ISBN 076952799X, 9780769527994

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Abstract

Searching for jobs online is an information intensive activity, because thousands of jobs are posted on the Web daily and it takes a great deal of effort to find the right position. Job search sites require recommender systems to meet diversified information needs: Job seekers who have well-defined careers try to focus on relevant open positions while students who have general and evolving interests want to follow the dominant trends of the job market in order to plan their career path. In this paper, we introduce a comprehensive job recommender system. From the user's perspective, four different kinds of recommendations are implemented. Users of this system can retrieve open jobs with different methods, ranging from exploring to searching. ©2007 IEEE.


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Details

Item Type: Book Section
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Lee, DHhyl12@pitt.eduHYL12
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 1 December 2007
Date Type: Publication
Journal or Publication Title: 3rd International Conference on Autonomic and Autonomous Systems, ICAS'07
Event Type: Conference
DOI or Unique Handle: 10.1109/conielecomp.2007.76
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 076952799X, 9780769527994
Date Deposited: 24 Apr 2012 13:58
Last Modified: 04 Feb 2019 15:58
URI: http://d-scholarship.pitt.edu/id/eprint/11974

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