Identifying relevant full-text articles for database curation

Chih Lee; Wen-Juan Hou; Hsin His Chen

Identifying relevant full-text articles for database curation

Chih Lee^*, Wen-Juan Hou, Hsin His Chen

^*Corresponding author for this work

Department of Computer Science and Information Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

In this paper, we propose an approach for identifying curatable articles from a large pool. Our system currently considers three parts of an article as three individual representations of the article, and utilizes two domain-specific resources to reveal the deep knowledge contained in the article in order to generate more representations of the article. Cross-validation is employed to find the best combination of representations and an SVM classifier is trained out of this combination. The cross-validation results and results of the official runs are listed. The experimental results show overall high performance.

Original language	English
Journal	NIST Special Publication
Publication status	Published - 2005 Dec 1
Event	14th Text REtrieval Conference, TREC 2005 - Gaithersburg, MD, United States Duration: 2005 Nov 15 → 2005 Nov 18

ASJC Scopus subject areas

Engineering(all)

Cite this

@article{d21d557131784f33b407da0a77cd953f,

title = "Identifying relevant full-text articles for database curation",

abstract = "In this paper, we propose an approach for identifying curatable articles from a large pool. Our system currently considers three parts of an article as three individual representations of the article, and utilizes two domain-specific resources to reveal the deep knowledge contained in the article in order to generate more representations of the article. Cross-validation is employed to find the best combination of representations and an SVM classifier is trained out of this combination. The cross-validation results and results of the official runs are listed. The experimental results show overall high performance.",

author = "Chih Lee and Wen-Juan Hou and Chen, {Hsin His}",

year = "2005",

month = dec,

day = "1",

language = "English",

journal = "NIST Special Publication",

issn = "1048-776X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "14th Text REtrieval Conference, TREC 2005 ; Conference date: 15-11-2005 Through 18-11-2005",

}

TY - JOUR

T1 - Identifying relevant full-text articles for database curation

AU - Lee, Chih

AU - Hou, Wen-Juan

AU - Chen, Hsin His

PY - 2005/12/1

Y1 - 2005/12/1

N2 - In this paper, we propose an approach for identifying curatable articles from a large pool. Our system currently considers three parts of an article as three individual representations of the article, and utilizes two domain-specific resources to reveal the deep knowledge contained in the article in order to generate more representations of the article. Cross-validation is employed to find the best combination of representations and an SVM classifier is trained out of this combination. The cross-validation results and results of the official runs are listed. The experimental results show overall high performance.

AB - In this paper, we propose an approach for identifying curatable articles from a large pool. Our system currently considers three parts of an article as three individual representations of the article, and utilizes two domain-specific resources to reveal the deep knowledge contained in the article in order to generate more representations of the article. Cross-validation is employed to find the best combination of representations and an SVM classifier is trained out of this combination. The cross-validation results and results of the official runs are listed. The experimental results show overall high performance.

UR - http://www.scopus.com/inward/record.url?scp=84873560638&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84873560638&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84873560638

JO - NIST Special Publication

JF - NIST Special Publication

SN - 1048-776X

T2 - 14th Text REtrieval Conference, TREC 2005

Y2 - 15 November 2005 through 18 November 2005

ER -

Identifying relevant full-text articles for database curation

Abstract

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this