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System for identifying and classifying denomination entity

A named entity and named entity recognition technology, applied in natural language analysis, special data processing applications, instruments, etc., can solve problems such as laborious, large maintenance work, and inability to deal with portability problems.

Inactive Publication Date: 2007-02-07
AGENCY FOR SCI TECH & RES
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This system is mostly rule-based and cannot handle portability issues and is very laborious
Each new text source requires a change in the rules to keep its performance constant, so such a system requires a lot of maintenance

Method used

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  • System for identifying and classifying denomination entity
  • System for identifying and classifying denomination entity
  • System for identifying and classifying denomination entity

Examples

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Embodiment Construction

[0027] In an embodiment described below, a hidden Markov model is used in named entity recognition (NER). Using the principle of limit relaxation, a pattern induction algorithm is used during training to induce effective patterns. Then, the induced pattern is used in the recognition process through the regression fixed modulus algorithm to solve the problem of data sparseness. Each feature is structured hierarchically in order to limit the relaxation process. As a result, the problem of data sparseness in named entity recognition can be effectively solved, and at the same time, the named entity recognition system can have better performance and better portability.

[0028] figure 1 It is a schematic block diagram of a named entity recognition system 10 according to an embodiment of the present invention. The named entity recognition system 10 includes a memory 12 for receiving and storing a text 14, which is sent from a scanner, the Internet, or some other network or some other ...

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PUM

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Abstract

A Hidden Markov Model is used in Named Entity Recognition (NER). Using the constraint relaxation principle, a pattern induction algorithm is presented in the training process to induce effective patterns. The induced patterns are then used in the recognition process by a back-off modelling algorithm to resolve the data sparseness problem. Various features are structured hierarchically to facilitate the constraint relaxation process. In this way, the data sparseness problem in named entity recognition can be resolved effectively and a named entity recognition system with better performance and better portability can be achieved.

Description

Technical field [0001] The present invention relates to Named Entity Recognition (NER), especially automatic pattern learning. Background technique [0002] Named entity recognition is used in natural language processing and information extraction to identify names in the text (Named Entitied----NEs), and classify these names into predetermined categories, such as "personal name" ", "location name", "organization name", "date", "time", "percentage", "money amount", etc. (there is usually a miscellaneous "other" for those that are not suitable for placing any Words in a specific category. In computer language, NER is a part of information extraction that extracts specific types of information from a document. Using named entity recognition, the specific information is the name of the entity, which constitutes the analysis of the document The main part, such as database retrieval. Therefore, precise naming is very important. [0003] Through the question forms in the sentence, such...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27
CPCG06F17/278G06F40/295G06F40/20
Inventor 周国栋苏俭
Owner AGENCY FOR SCI TECH & RES
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