Training parsers to approximately optimize NDCG
    1.
    发明授权
    Training parsers to approximately optimize NDCG 有权
    训练解析器大致优化NDCG

    公开(公告)号:US08473486B2

    公开(公告)日:2013-06-25

    申请号:US12962751

    申请日:2010-12-08

    IPC分类号: G06F7/00 G06F17/30

    CPC分类号: G06F17/30864

    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.

    摘要翻译: 监督技术使用相关性判断来训练依赖性解析器,使得它在信息检索中大致优化归一化折扣累积增益(NDCG)。 用于查询的解析树和文档的解析树之间的加权树编辑距离被添加到排序函数,其中编辑距离权重是来自解析器的参数。 在排序函数中使用解析器参数可以通过向目标函数添加一些约束来近似优化NDCG的解析器参数。

    TRAINING PARSERS TO APPROXIMATELY OPTIMIZE NDCG
    2.
    发明申请
    TRAINING PARSERS TO APPROXIMATELY OPTIMIZE NDCG 有权
    训练员大大优化NDCG

    公开(公告)号:US20120150836A1

    公开(公告)日:2012-06-14

    申请号:US12962751

    申请日:2010-12-08

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30864

    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.

    摘要翻译: 监督技术使用相关性判断来训练依赖性解析器,使得它在信息检索中大致优化归一化折扣累积增益(NDCG)。 用于查询的解析树和文档的解析树之间的加权树编辑距离被添加到排序函数,其中编辑距离权重是来自解析器的参数。 在排序函数中使用解析器参数可以通过向目标函数添加一些约束来近似优化NDCG的解析器参数。