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Zhou, L.; Zhang, D.: NLPIR: a theoretical framework for applying Natural Language Processing to information retrieval (2003) 0.00
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Abstract

Zhou and Zhang believe that for the potential of natural language processing NLP to be reached in information retrieval a framework for guiding the effort should be in place. They provide a graphic model that identifies different levels of natural language processing effort during the query, document matching process. A direct matching approach uses little NLP, an expansion approach with thesauri, little more, but an extraction approach will often use a variety of NLP techniques, as well as statistical methods. A transformation approach which creates intermediate representations of documents and queries is a step higher in NLP usage, and a uniform approach, which relies on a body of knowledge beyond that of the documents and queries to provide inference and sense making prior to matching would require a maximum NPL effort.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.2, S.115-123

Tao, J.; Zhou, L.; Hickey, K.: Making sense of the black-boxes : toward interpretable text classification using deep learning models (2023) 0.00

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Source: Journal of the Association for Information Science and Technology. 74(2023) no.6, S.685-700

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