发明授权
- 专利标题: Training parsers to approximately optimize NDCG
- 专利标题(中): 训练解析器大致优化NDCG
-
申请号: US12962751申请日: 2010-12-08
-
公开(公告)号: US08473486B2公开(公告)日: 2013-06-25
- 发明人: Xiaodong He , Jianfeng Gao , Jennifer Gillenwater
- 申请人: Xiaodong He , Jianfeng Gao , Jennifer Gillenwater
- 申请人地址: US WA Redmond
- 专利权人: Microsoft Corporation
- 当前专利权人: Microsoft Corporation
- 当前专利权人地址: US WA Redmond
- 代理机构: Turk IP Law, LLC
- 主分类号: G06F7/00
- IPC分类号: G06F7/00 ; G06F17/30
摘要:
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.
公开/授权文献
- US20120150836A1 TRAINING PARSERS TO APPROXIMATELY OPTIMIZE NDCG 公开/授权日:2012-06-14
信息查询