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    STUDIA INFORMATICA - Issue no. 2 / 2011  
         
  Article:   ISSUES IN TOPIC TRACKING IN WIKIPEDIA ARTICLES.

Authors:  CONSTANTIN ORĂSAN.
 
       
         
  Abstract:  

INTRODUCTION. In the last few years, Wikipedia has become a very useful resource for NLP offering access to both structured and unstructured information that can be used for further language processing. One particularity of the Wikipedia articles is that they focus on only one topic (e.g. a product, person, location or event), which is detailed throughout the article. In order to extract comprehensive information from these articles, it is necessary to be able to track different expressions that refer to the topic. This paper discusses the issues to be tackled when a topic tracking algorithm is implemented. In order to address this problem, a shallow rule-based coreference resolution method for topic tracking was implemented.

Key words and phrases. coreference resolution, Wikipedia, near identity.

 
         
     
         
         
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