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首页> 外文期刊>Journal of the American Society for Information Science >NLPIR: A Theoretical Framework for Applying Natural Language Processing to Information Retrieval
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NLPIR: A Theoretical Framework for Applying Natural Language Processing to Information Retrieval

机译:NLPIR:将自然语言处理应用于信息检索的理论框架

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摘要

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.
机译:信息检索(IR)在支持决策和知识管理中的作用越来越重要。面对传统的基于关键字的IR中的各种问题,许多研究人员一直在研究自然语言处理(NLP)技术的潜力。尽管NLP在IR中得到了广泛的应用,并且人们对NLP可以解决传统IR的问题寄予很高的期望,但是用于IR系统的NLP组件的研究和开发仍然缺乏凝聚力框架的支持和指导。在本文中,我们提出了一个称为NLPIR的理论框架,旨在将NLP集成到IR中,并广泛推广NLP在IR中的广泛应用。描述了一些现有的NLP技术以验证该框架,该技术不仅可以应用于当前研究,而且可以预见为支持涉及NLP的IR的未来研究和开发。

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