Invention Grant
- Patent Title: Directly optimizing evaluation measures in learning to rank
- Patent Title (中): 直接优化学习排名评估指标
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Application No.: US12237293Application Date: 2008-09-24
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Publication No.: US08478748B2Publication Date: 2013-07-02
- Inventor: Jun Xu , Tie-Yan Liu , Hang Li
- Applicant: Jun Xu , Tie-Yan Liu , Hang Li
- Applicant Address: US WA Redmond
- Assignee: Microsoft Corporation
- Current Assignee: Microsoft Corporation
- Current Assignee Address: US WA Redmond
- Agency: Perkins Coie LLP
- Main IPC: G06F17/30
- IPC: G06F17/30

Abstract:
The present invention provides methods for improving a ranking model. In one embodiment, a method includes the step of obtaining queries, documents, and document labels. The process then initializes active sets using the document labels, wherein two active sets are established for each query, a perfect active set and an imperfect active set. Then, the process optimizes an empirical loss function by the use of the first and second active set, whereby parameters of the ranking model are modified in accordance to the empirical loss function. The method then updates the active sets with additional ranking data, wherein the updates are configured to work in conjunction with the optimized loss function and modified ranking model. The recalculated active sets provide an indication for ranking the documents in a way that is more consistent with the document metadata.
Public/Granted literature
- US20100082606A1 DIRECTLY OPTIMIZING EVALUATION MEASURES IN LEARNING TO RANK Public/Granted day:2010-04-01
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