License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
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DOI: 10.4230/OASIcs.ICCSW.2018.5
URN: urn:nbn:de:0030-drops-101866
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Mohasseb, Alaa ; Bader-El-Den, Mohamed ; Cocea, Mihaela

Towards Context-Aware Syntax Parsing and Tagging

OASIcs-ICCSW-2018-5.pdf (0.5 MB)


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.

BibTeX - Entry

  author =	{Alaa Mohasseb and Mohamed Bader-El-Den and Mihaela Cocea},
  title =	{{Towards Context-Aware Syntax Parsing and Tagging}},
  booktitle =	{2018 Imperial College Computing Student Workshop (ICCSW 2018)},
  pages =	{5:1--5:9},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-097-2},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{66},
  editor =	{Edoardo Pirovano and Eva Graversen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-101866},
  doi =		{10.4230/OASIcs.ICCSW.2018.5},
  annote =	{Keywords: Information Retrieval, Natural Language Processing, PoS Tagging, PoS Parsing, Machine Learning}

Keywords: Information Retrieval, Natural Language Processing, PoS Tagging, PoS Parsing, Machine Learning
Collection: 2018 Imperial College Computing Student Workshop (ICCSW 2018)
Issue Date: 2019
Date of publication: 25.01.2019

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