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Research on Named Entity Recognition Based on Rules

Author: ZhouKun
Tutor: HuXueGang
School: Hefei University of Technology
Course: Computer Software and Theory
Keywords: Chinese information processing Named Entity Recognition Chinese word segmentation Noumenon
CLC: TP391.1
Type: Master's thesis
Year: 2010
Downloads: 161
Quote: 2
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Abstract


Chinese word segmentation is the first step in natural language processing . In practical applications , segmentation constrained by many factors , unknown words segmentation is one of the important factors to influence the segmentation correct rate . The main form of unknown words , including place names , organization names named entity . Therefore, the identification of named entities fusion to Chinese word segmentation process plays an important role to improve the accuracy of Chinese word . In addition , the study named entity recognition , information extraction , information retrieval , machine translation , text classification applications achieve has important theoretical and practical value . This article 's main research contents are as follows : (1) propose a fusion named entity recognition of Chinese sub- word model , word segmentation process at the same time carry out identification of named entities , reducing the named entities, etc. are not logged word of recognition errors and cause the Chinese lexical segmentation errors, thus improving the accuracy of the segmentation . (2) hierarchical classification system , based ontology building the knowledge base of Chinese names , Chinese names field of knowledge is divided into several levels , low levels of the field of knowledge is the basis of the high-level , high-level domain knowledge is the low level of generalization and summarization , effectively improve the names Knowledge Base maintainability . ( 3 ) build a rule base named entity recognition , using the rule - matching method to identify named entities . Recognition system has self-learning ability , while identifying named entities recognition results can be analyzed to generate to feedback new rules to the rule base , has a good effect of named entity recognition .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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