Difference between revisions of "Title Named Entity Recognition Using Wikipedia and Abbreviation Generation"

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'''Title Named Entity Recognition Using Wikipedia and Abbreviation Generation''' - scientific work related to Wikipedia quality published in 2014, written by Youngmin Park, Sangwoo Kang and Jungyun Seo.
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'''Title Named Entity Recognition Using Wikipedia and Abbreviation Generation''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[Youngmin Park]], [[Sangwoo Kang]] and [[Jungyun Seo]].
  
 
== Overview ==
 
== Overview ==
In this paper, authors propose a title named entity recognition model using Wikipedia and abbreviation generation. The proposed title named entity recognition model automatically extracts title named entities from Wikipedia so constant renewal is possible without additional costs. Also, in order to establish a dictionary of title named entity abbreviations, generation rules are used to generate abbreviation candidates and abbreviations are selected through web search methods. In this paper, authors propose a statistical model that recognizes title named entities using CRFs (Conditional Random Fields). The proposed model uses lexical information, a named entity dictionary, and an abbreviation dictionary, and provides title named entity recognition performance of 82.1% according to experimental results.
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In this paper, authors propose a title [[named entity recognition]] model using [[Wikipedia]] and abbreviation generation. The proposed title [[named entity]] recognition model automatically extracts title [[named entities]] from Wikipedia so constant renewal is possible without additional costs. Also, in order to establish a dictionary of title named entity abbreviations, generation rules are used to generate abbreviation candidates and abbreviations are selected through web search methods. In this paper, authors propose a statistical model that recognizes title named entities using CRFs (Conditional Random Fields). The proposed model uses lexical information, a named entity dictionary, and an abbreviation dictionary, and provides title named [[entity recognition]] performance of 82.1% according to experimental results.

Revision as of 00:42, 10 November 2019

Title Named Entity Recognition Using Wikipedia and Abbreviation Generation - scientific work related to Wikipedia quality published in 2014, written by Youngmin Park, Sangwoo Kang and Jungyun Seo.

Overview

In this paper, authors propose a title named entity recognition model using Wikipedia and abbreviation generation. The proposed title named entity recognition model automatically extracts title named entities from Wikipedia so constant renewal is possible without additional costs. Also, in order to establish a dictionary of title named entity abbreviations, generation rules are used to generate abbreviation candidates and abbreviations are selected through web search methods. In this paper, authors propose a statistical model that recognizes title named entities using CRFs (Conditional Random Fields). The proposed model uses lexical information, a named entity dictionary, and an abbreviation dictionary, and provides title named entity recognition performance of 82.1% according to experimental results.