【摘要】 传统的信息检索模型假设查询中的关键词之间是并列关系,但用户的需求往往应该被抽象为一系列的关键词组,组内的关键词间具有更为紧密的语义关系,这就是定义的临近词检索问题。提出了基于权重矩阵的临近词检索问题解决框架,该框架将文档和查询抽象化为文档的权重矩阵表示和查询权重矩阵,通过计算两个矩阵间的相似度来实现临近词检索。实验结果证明,针对临近词检索问题,传统的信息检索模型只是一种简化问题的解决方案,权重矩阵框架从理论上和形式上更加契合临近词检索问题,查准率得到了显著的提高。更多还原

【Abstract】 Tradional information retrieval models assume that keywords in queries are parallel,but the requirements of users should be abstracted to a series of keywords groups,and the sematic relations of keywords inside the group are closer than outside.This is "Term Proximity Information Retrieval"(TPIR) defined in this paper,and we presented a solution framework based on Weigh Matrix(WMSF).WMSF abstractes documents and queries to Weigh Matrix Representation of Document and Query Weigh Matrix,and then implements the TPIR based on the caculating of similarity between them.Empirical results show that WMSF is appropriate for TPIR compared with traditional information retrieval models which simplify the TPIR problems actually更多还原