Towards Context-Aware Syntax Parsing and Tagging

Authors Alaa Mohasseb, Mohamed Bader-El-Den, Mihaela Cocea

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Alaa Mohasseb
  • School of Computing, University of Portsmouth, United Kingdom
Mohamed Bader-El-Den
  • School of Computing, University of Portsmouth, United Kingdom
Mihaela Cocea
  • School of Computing, University of Portsmouth, United Kingdom

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Alaa Mohasseb, Mohamed Bader-El-Den, and Mihaela Cocea. Towards Context-Aware Syntax Parsing and Tagging. In 2018 Imperial College Computing Student Workshop (ICCSW 2018). Open Access Series in Informatics (OASIcs), Volume 66, pp. 5:1-5:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Natural language processing
  • Information Retrieval
  • Natural Language Processing
  • PoS Tagging
  • PoS Parsing
  • Machine Learning


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