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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lee, D.H. Brusilovsky, P. |
| Copyright Year | 2007 |
| Description | Author affiliation: Univ. of Pittsburgh, Pittsburgh (Lee, D.H.; Brusilovsky, P.) |
| 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. |
| Starting Page | 21 |
| Ending Page | 21 |
| File Size | 976952 |
| Page Count | 1 |
| File Format | |
| ISBN | 0769528597 |
| DOI | 10.1109/CONIELECOMP.2007.76 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-06-19 |
| Publisher Place | Greece |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Mass production Mass customization information retrieval from multiple views Engineering profession Humans Information retrieval Remuneration Job recommender Silver exploratory search Needles Internet Recommender systems |
| Content Type | Text |
| Resource Type | Article |
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