关键词: 向量空间模型, 语义分组, 信息检索, 查准率, 查全率

Abstract:

Based on the structural and content feature of Web news information and the analysis of the insufficiency of the traditional vector space model,this paper proposes an improved vector space model that the semantic group is formed according to the characteristic word.This model divides the characteristic word of a report into four relatively independent groups according to the semantic meaning:time,place,character and event,and thus forms four vector spaces.Then the characteristic weight and the similarity to each vector space are calculated.Theoretical analysis and the experimental results show that the improvement of the model adapts better to Web news information retrieval,thus improving the precision,recall and computation speed.

Key words: vector space model;semantic group;information retrieval;precision;recall