Personalised Retrieval for Online Recruitment Services
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|Title:||Personalised Retrieval for Online Recruitment Services||Authors:||Rafter, Rachael
|Permanent link:||http://hdl.handle.net/10197/4636||Date:||5-Apr-2000||Online since:||2013-10-01T09:01:52Z||Abstract:||Internet search technology is largely based on exact-match retrieval. Such systems rely on the user to provide an adequate description of their requirements. However, most users submit poorly specified queries, leading to imprecise search results. Furthermore, there is no facility for personalising searches to reflect implicit likes and dislikes of users. We describe two complementary solutions to these problems as implemented in CASPER, an intelligent online recruitment service. We describe an approach to personalised similarity-based retrieval, and a queryless collaborative filtering recommendation technique.||Type of material:||Conference Publication||Keywords:||Personalised Retrieval; Recruitment Services||Language:||en||Status of Item:||Not peer reviewed||Is part of:||Proceedings of the 22nd Annual Colloquium on Information Retrieval. 2000.||Conference Details:||The BCS/ IRSG 22nd Annual Colloquium on Information Retrieval (IRSG 2000), Cambridge, UK, 5-7 April, 2000|
|Appears in Collections:||Computer Science Research Collection|
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