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Study on Chinese Name Entity Recognition and Some Related Issues

Author: YangXiaoDong
Tutor: ZuoLi
School: Jiangsu University
Course: Applied Computer Technology
Keywords: Chinese Named Entity Recognition Part- type Referred to as identification Conditional Random Fields Support Vector Machine
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 141
Quote: 1
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Abstract


Named entities are important linguistic units carrying information in natural language. Chinese named entity recognition is one of the key technologies of the Chinese information processing, with the Chinese named entity widely used in various fields, it is both a basic research is an applied research of high value. At present, the Chinese name recognition encountered a problem named entity recognition of the many influencing factors leading to poor results with the complex structure of named entity recognition; Although many existing methods, but the Chinese named entity recognition is still not achieve the ideal state. The named entity names, places identification expanded more mature, organization name recognition is not ideal. Get characterized in face of the complex structure organization name to construct the corresponding model, and the use of these characteristics to solve the problem of identification of the institution name, and it is particularly important to improve the deficiencies of the existing methods. First of all, the use of cascading conditions random field model to handle text as a sequence of observations advantage of the underlying conditions of the observed value of the random field model to do a preliminary names, place names identification, and then use the result of recognition passed to the top as a high-level observations further organization name recognition; fusion rules in the stacked condition between the random field model to deal with a certain regularity properties of named entity; conditions in the face of the introduction of the time-consuming problem with the airport model training a fast training methods. Misidentification of the complex organization name, pointing out that its influencing factors, and named entities for which one of the factors (part type) to further study the use of SVM model on the advantages of the binary classification type names, place names preliminary recognition; difficult to identify and referred to this organization name recognition factors affecting the preliminary analysis, according to the characteristics of short and full names of word formation the context word formation characteristics, given a context word formation boot table combined with the full name of the matching method to identify the short name. Finally, names, organization name recognition of the type of Onomastic referred to identify related experiments. For place names, the name of your organization, from different corpus, template, part of speech characteristics CRF model-based experimental comparison, given this paper a new method and the comparison of the existing methods: description of the training and rules to optimize the experimental results to verify each optimize the effectiveness of the method; Chief type names, place names recognition and simply identify experimental results and give a preliminary analysis. The experiments show that this method is effective, there is a certain significance for Chinese information processing.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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