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  • 标题:Towards Context-Aware Syntax Parsing and Tagging
  • 本地全文:下载
  • 作者:Alaa Mohasseb ; Mohamed Bader-El-Den ; Mihaela Cocea
  • 期刊名称:OASIcs : OpenAccess Series in Informatics
  • 电子版ISSN:2190-6807
  • 出版年度:2019
  • 卷号:66
  • 页码:1-9
  • DOI:10.4230/OASIcs.ICCSW.2018.5
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:Information retrieval (IR) has become one of the most popular Natural Language Processing (NLP) applications. Part of speech (PoS) parsing and tagging plays an important role in IR systems. A broad range of PoS parsers and taggers tools have been proposed with the aim of helping to find a solution for the information retrieval problems, but most of these are tools based on generic NLP tags which do not capture domain-related information. In this research, we present a domain-specific parsing and tagging approach that uses not only generic PoS tags but also domain-specific PoS tags, grammatical rules, and domain knowledge. Experimental results show that our approach has a good level of accuracy when applying it to different domains.
  • 关键词:Information Retrieval; Natural Language Processing; PoS Tagging; PoS Parsing; Machine Learning
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