基于查询日志的语义关系发现算法
iscovering Semantic Relations from Query Logs
提出了基于查询日志的语义关系发现算法，通过对搜索引擎查询日志分析，构建查询词与URL的双向图，使用图距离结合同义相似度计算查询词的语义相似度，同时采用基于路径的高效图挖掘算法实现查询词的语义关系发现。采用sogou近2000万条记录用户查询点击记录的日志实验表明，该算法较子串扩展算法与日志挖掘算法有更好的准确率与查全率。
discovering semantic relations algorithm from Query Logs is presented. First construct a weighted Query-URL bipartite graph from query log data. Then compute the semantic similarity of queries by distance of queries nodes and synonymy similarity and use a effective mining algorithm to discovering semantic related queries based on graph path. Experiments show that the algorithm is more effective than substring extending algorithm and log mining algorithm in recall and precision.
肖达、王枞、刘建毅、伍淳华、贺海波、杨义先
计算技术、计算机技术
查询日志词语相似度基于路径的图挖掘语义关系发现
query logssemantic similaritymining algorithm based on graph pathsemantic relations discovering.
肖达,王枞,刘建毅,伍淳华,贺海波,杨义先.基于查询日志的语义关系发现算法[EB/OL].(2009-07-13)[2025-08-11].http://www.paper.edu.cn/releasepaper/content/200907-265.点此复制
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