A rule-based approach for automatic identification of publication types of medical papers

Abeed Sarker; Diego Molla-Aliod

A rule-based approach for automatic identification of publication types of medical papers

Abeed Sarker^*, Diego Molla-Aliod

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

8 Citations (Scopus)

Abstract

The medical domain has an abundance of textual resources of varying quality. The quality of medical articles depends largely on their publication types. However, identifying high-quality medical articles from search results is till date a manual and time-consuming process. We present a simple, rule-based, post-retrieval approach to automatically identify medical articles belonging to three high-quality publication types. Our approach simply uses title and abstract information of the articles to perform this. Our experiments show that such a rule-based approach has close to 100% precision and recall for the three publication types.

Original language	English
Title of host publication	ADCS 2010 - Proceedings of the Fifteenth Australasian Document Computing Symposium
Editors	Falk Scholer, Andrew Trotman, Andrew Turpin
Place of Publication	Melbourne, Australia
Publisher	RMIT University
Pages	84-88
Number of pages	5
ISBN (Print)	9781921426803
Publication status	Published - 2010
Event	15th Australasian Document Computing Symposium, ADCS 2010 - Melbourne, VIC, Australia Duration: 10 Dec 2008 → 10 Dec 2008

Other

Other	15th Australasian Document Computing Symposium, ADCS 2010
Country/Territory	Australia
City	Melbourne, VIC
Period	10/12/08 → 10/12/08

Cite this

@inproceedings{47ce5f74df9043eaa7f45c7be4661d03,

title = "A rule-based approach for automatic identification of publication types of medical papers",

abstract = "The medical domain has an abundance of textual resources of varying quality. The quality of medical articles depends largely on their publication types. However, identifying high-quality medical articles from search results is till date a manual and time-consuming process. We present a simple, rule-based, post-retrieval approach to automatically identify medical articles belonging to three high-quality publication types. Our approach simply uses title and abstract information of the articles to perform this. Our experiments show that such a rule-based approach has close to 100% precision and recall for the three publication types.",

author = "Abeed Sarker and Diego Molla-Aliod",

year = "2010",

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editor = "Falk Scholer and Andrew Trotman and Andrew Turpin",

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publisher = "RMIT University",

note = "15th Australasian Document Computing Symposium, ADCS 2010 ; Conference date: 10-12-2008 Through 10-12-2008",

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Sarker, A & Molla-Aliod, D 2010, A rule-based approach for automatic identification of publication types of medical papers. in F Scholer, A Trotman & A Turpin (eds), ADCS 2010 - Proceedings of the Fifteenth Australasian Document Computing Symposium. RMIT University, Melbourne, Australia, pp. 84-88, 15th Australasian Document Computing Symposium, ADCS 2010, Melbourne, VIC, Australia, 10/12/08.

A rule-based approach for automatic identification of publication types of medical papers. / Sarker, Abeed; Molla-Aliod, Diego.
ADCS 2010 - Proceedings of the Fifteenth Australasian Document Computing Symposium. ed. / Falk Scholer; Andrew Trotman; Andrew Turpin. Melbourne, Australia: RMIT University, 2010. p. 84-88.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Molla-Aliod, Diego

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AB - The medical domain has an abundance of textual resources of varying quality. The quality of medical articles depends largely on their publication types. However, identifying high-quality medical articles from search results is till date a manual and time-consuming process. We present a simple, rule-based, post-retrieval approach to automatically identify medical articles belonging to three high-quality publication types. Our approach simply uses title and abstract information of the articles to perform this. Our experiments show that such a rule-based approach has close to 100% precision and recall for the three publication types.

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M3 - Conference proceeding contribution

AN - SCOPUS:84872872022

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BT - ADCS 2010 - Proceedings of the Fifteenth Australasian Document Computing Symposium

A2 - Scholer, Falk

A2 - Trotman, Andrew

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T2 - 15th Australasian Document Computing Symposium, ADCS 2010

Y2 - 10 December 2008 through 10 December 2008

ER -

A rule-based approach for automatic identification of publication types of medical papers

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