NDLI: Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection

Content Provider	PubMed Central
Author	Chen, Yifei Sun, Yuxing Han, Bing-qing
Copyright Year	2015
Abstract	Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.
Related Links	http://dx.doi.org/10.1155/2015/751646
Starting Page	751646
File Format	PDF
ISSN	23146133
e-ISSN	23146141
Journal	BioMed Research International
Volume Number	2015
Language	English
Publisher	Hindawi Publishing Corporation
Publisher Date	2015-01-01
Access Restriction	Open
Rights Holder	Hindawi Publishing Corporation
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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