词性标注对信息检索系统性能的影响

在信息检索中引入NLP 技术是信息检索发展的主要趋势,本文将NLP 中较为成熟的词性标注技术加入信息检索,采用大规模TREC 数据集,试图发现词性标注对检索系统性能的影响。笔者在SMART 检索系统上使用不同标注集、不同索引项权重进行了检索实验。实验表明,在信息检索中加入词性标注信息可能会对某些特定Topic 和Document 的检索效果有所改进,但词性标注的影响能力弱于索引项权重选择的影响能力。词性标注对检索性能的影响涉及到Topic 和Document 中的具体用词,普遍规律有待进一步研究。

Effects of POS Tagging on Performance of IR Systems

NLP technology combined with information retrieval has become mainstream in the IR field.In this article,the authors combine POS tagging with IR,in an attempt to find the effects of POS tagging on the performance of IR systems.Using the SMART system,the authors performed experiments with different tagsets and different term vector weighting schemes.According to the experiments,we found that retrieval performance using tags improved in certain topics and documents.The effects,however,are inferior to the assignment of appropriate term weighting.The effects concern concrete words in topics and documents.We still need further research to find general rules.