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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Malinowski, J. Keim, T. Wendt, O. Weitzel, T. |
| Copyright Year | 2006 |
| Description | Author affiliation: University of Frankfurt (Malinowski, J.) |
| Abstract | Recommendation systems are widely used on the Internet to assist customers in finding the products or services that best fit with their individual preferences. While current implementations successfully reduce information overload by generating personalized suggestions when searching for objects such as books or movies, recommendation systems so far cannot be found in another potential field of application: the personalized search for subjects such as applicants in a recruitment scenario. Theory shows that a good match between persons and jobs needs to consider both, the preferences of the recruiter and the preferences of the candidate. Based on this requirement for modeling bilateral selection decisions, we present an approach applying two distinct recommendation systems to the field in order to improve the match between people and jobs. Finally, we present first validation test runs from a student experiment showing promising results. |
| File Size | 262420 |
| File Format | |
| ISBN | 0769525075 |
| ISSN | 15301605 |
| DOI | 10.1109/HICSS.2006.266 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-01-04 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Recruitment Information systems Student experiments Collaboration Information filtering Information filters Concrete Web and internet services Books Motion pictures |
| Content Type | Text |
| Resource Type | Article |
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