NLPIR: a Theoretical Framework for Applying Natural Language Processing to Information Retrieval
NLPIR: a Theoretical Framework for Applying Natural Language Processing to Information Retrieval
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DOI：
10.1002/asi.10193
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
Lina Zhou;Dongsong Zhang
中科院分区：
文献类型：
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作者：
Lina Zhou;Dongsong Zhang
信息检索(IR)在支持决策和知识管理方面的作用越来越重要。面对传统的基于关键词的信息检索存在的各种问题，许多研究人员开始研究自然语言处理(NLP)技术的潜力。尽管NLP在信息检索中得到了广泛的应用，人们对NLP能够解决传统信息检索的问题寄予了很高的期望，但用于信息检索系统的NLP组件的研究和开发仍然缺乏一个连贯的框架的支持和指导。在本文中，我们提出了一个称为NLPIR的理论框架，旨在将NLP整合到信息检索中，并推广NLP在信息检索中的广泛应用。描述了一些现有的自然语言处理技术来验证该框架，该框架不仅可以应用于当前的研究，而且可以支持未来涉及自然语言处理的信息检索的研究和开发。
The role of information retrieval (IR) in support of decision making and knowledge management has become increasingly significant. Confronted by various problems in traditional keyword-based IR, many researchers have been investigating the potential of natural language processing (NLP) technologies. Despite widespread application of NLP in IR and high expectations that NLP can address the problems of traditional IR, research and development of an NLP component for an IR system still lacks support and guidance from a cohesive framework. In this paper, we propose a theoretical framework called NLPIR that aims at integrating NLP into IR and at generalizing broad application of NLP in IR. Some existing NLP techniques are described to validate the framework, which not only can be applied to current research, but is also envisioned to support future research and development in IR that involve NLP.