Invention Grant
- Patent Title: Training parsers to approximately optimize NDCG
- Patent Title (中): 训练解析器大致优化NDCG
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Application No.: US12962751Application Date: 2010-12-08
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Publication No.: US08473486B2Publication Date: 2013-06-25
- Inventor: Xiaodong He , Jianfeng Gao , Jennifer Gillenwater
- Applicant: Xiaodong He , Jianfeng Gao , Jennifer Gillenwater
- Applicant Address: US WA Redmond
- Assignee: Microsoft Corporation
- Current Assignee: Microsoft Corporation
- Current Assignee Address: US WA Redmond
- Agency: Turk IP Law, LLC
- Main IPC: G06F7/00
- IPC: G06F7/00 ; G06F17/30

Abstract:
A supervised technique uses relevance judgments to train a dependency parser such that it approximately optimizes Normalized Discounted Cumulative Gain (NDCG) in information retrieval. A weighted tree edit distance between the parse tree for a query and the parse tree for a document is added to a ranking function, where the edit distance weights are parameters from the parser. Using parser parameters in the ranking function enables approximate optimization of the parser's parameters for NDCG by adding some constraints to the objective function.
Public/Granted literature
- US20120150836A1 TRAINING PARSERS TO APPROXIMATELY OPTIMIZE NDCG Public/Granted day:2012-06-14
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