| Publisher | Association for Computing Machinery | ||
|---|---|---|---|
| Format | 268.9KB PDF | Date added | 06 Aug 2006 |
| Topics | IT HR - Staffing - Training | ||
| Downloads | 49 | ||
The paper is concerned with applying learning to rank to document retrieval. Ranking SVM is a typical method of learning to rank. The authors point out that there are two factors one must consider when applying Ranking SVM, in general a "Learning to rank" method, to document retrieval. First, correctly ranking documents on the top of the result list is crucial for an Information Retrieval system. One must conduct training in a way that such ranked results are accurate. Second, the number of relevant documents can vary from query to query. One must avoid training a model biased toward queries with a large number of relevant documents.
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