Staff View: A prototype for context identification of scientific papers via agent-based text mining

A prototype for context identification of scientific papers via agent-based text mining

In many circumstances, it is quite challenging for researchers to look for papers that match their interests when searched from databases. More often, papers which have been searched are perused individually to precisely identify the relevant contents. In this paper, we present a prototype to test o...

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Main Authors:	Mahmoud, M.A., Ahmad, M.S.
Format:	Conference Paper
Language:	English
Published:	2017
Subjects:	Agent-based simulation Context Identification Data Mining Text Mining
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id	my.uniten.dspace-666
record_format	dspace
spelling	my.uniten.dspace-6662018-12-12T03:10:15Z A prototype for context identification of scientific papers via agent-based text mining Mahmoud, M.A. Ahmad, M.S. Agent-based simulation Context Identification Data Mining Text Mining In many circumstances, it is quite challenging for researchers to look for papers that match their interests when searched from databases. More often, papers which have been searched are perused individually to precisely identify the relevant contents. In this paper, we present a prototype to test our work-in-progress of an agent-based text mining algorithm that extracts and identifies the context of potentially relevant papers published in the WWW. The prototype involves an interface that enables a user to test the algorithm and view the results. The interface links to an abstract of a paper that the algorithm mines. We conduct tests on three abstracts of selected papers from the literature. We conduct the tests on various threshold settings that filter unnecessary data. The results show that the algorithm successfully identifies the contexts of the tested abstracts with thresholds of between 30%-60%. © 2016 IEEE. 2017-08-04T07:05:01Z 2017-08-04T07:05:01Z 2017 Conference Paper 10.1109/ISAMSR.2016.7810000 en 2nd International Symposium on Agent, Multi-Agent Systems and Robotics
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
language	English
topic	Agent-based simulation Context Identification Data Mining Text Mining
spellingShingle	Agent-based simulation Context Identification Data Mining Text Mining Mahmoud, M.A. Ahmad, M.S. A prototype for context identification of scientific papers via agent-based text mining
description	In many circumstances, it is quite challenging for researchers to look for papers that match their interests when searched from databases. More often, papers which have been searched are perused individually to precisely identify the relevant contents. In this paper, we present a prototype to test our work-in-progress of an agent-based text mining algorithm that extracts and identifies the context of potentially relevant papers published in the WWW. The prototype involves an interface that enables a user to test the algorithm and view the results. The interface links to an abstract of a paper that the algorithm mines. We conduct tests on three abstracts of selected papers from the literature. We conduct the tests on various threshold settings that filter unnecessary data. The results show that the algorithm successfully identifies the contexts of the tested abstracts with thresholds of between 30%-60%. © 2016 IEEE.
format	Conference Paper
author	Mahmoud, M.A. Ahmad, M.S.
author_facet	Mahmoud, M.A. Ahmad, M.S.
author_sort	Mahmoud, M.A.
title	A prototype for context identification of scientific papers via agent-based text mining
title_short	A prototype for context identification of scientific papers via agent-based text mining
title_full	A prototype for context identification of scientific papers via agent-based text mining
title_fullStr	A prototype for context identification of scientific papers via agent-based text mining
title_full_unstemmed	A prototype for context identification of scientific papers via agent-based text mining
title_sort	prototype for context identification of scientific papers via agent-based text mining
publishDate	2017
_version_	1644492310947299328
score	13.222552

A prototype for context identification of scientific papers via agent-based text mining

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