Syntactic Information Retrieval

Chang Liu, Hui Wang, S. McClean, Jun Liu, Shengli Wu
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引用次数: 11

Abstract

Natural language processing (NLP) techniques are believed to have the potential to aid information retrieval (IR) in terms of retrieval accuracy. In this paper we report a proof of concept study on a new approach to NLP-based IR that we propose. Documents and queries are represented as syntactic parse trees, which are generated by a natural language parser. Based on this tree structured representation of documents and queries, the matching between a document and a query is executed on their tree representations, with tree comparison as the key operation. An IR experiment is designed to test if this approach is feasible. Experimental results show that this approach is promising and has the potential to outperform the standard bag of words approach to information retrieval, especially in response to long queries.
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自然语言处理(NLP)技术被认为在检索精度方面具有帮助信息检索(IR)的潜力。在本文中,我们报告了我们提出的基于nlp的IR新方法的概念验证研究。文档和查询表示为语法解析树,由自然语言解析器生成。基于文档和查询的这种树状结构表示,在文档和查询的树状表示上执行文档和查询之间的匹配,以树比较作为关键操作。设计了一个红外实验来测试这种方法是否可行。实验结果表明,该方法很有前途,在信息检索方面具有优于标准词包方法的潜力,特别是在响应长查询时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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