Protein-protein interactions classification from text via local learning with class priors

Yulan He, Chenghua Lin

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

Abstract

Text classification is essential for narrowing down the number of documents relevant to a particular topic for further pursual, especially when searching through large biomedical databases. Protein-protein interactions are an example of such a topic with databases being devoted specifically to them. This paper proposed a semi-supervised learning algorithm via local learning with class priors (LL-CP) for biomedical text classification where unlabeled data points are classified in a vector space based on their proximity to labeled nodes. The algorithm has been evaluated on a corpus of biomedical documents to identify abstracts containing information about protein-protein interactions with promising results. Experimental results show that LL-CP outperforms the traditional semisupervised learning algorithms such as SVMand it also performs better than local learning without incorporating class priors.
Original languageEnglish
Title of host publicationNatural language processing and information systems
Subtitle of host publication14th international conference on applications of natural language to information systems, NLDB 2009, Saarbrücken, Germany, June 24-26, 2009. Revised Papers
EditorsHelmut Horacek, Elisabeth Métais, Rafael Muñoz, Magdalena Wolska
PublisherSpringer
Pages182-191
Number of pages10
Volume5723
ISBN (Print)3-642-12549-2, 978-3-642-12549-2
DOIs
Publication statusPublished - 2009
Event14th international conference on applications of natural language to information systems, NLDB 2009 - Saarbrücken, Germany
Duration: 24 Jun 200926 Jun 2009

Publication series

NameLecture notes in computer science
PublisherSpringer
Volume5723
ISSN (Print)0302-9743

Conference

Conference14th international conference on applications of natural language to information systems, NLDB 2009
CountryGermany
CitySaarbrücken
Period24/06/0926/06/09

Keywords

  • text classification
  • protein-protein interactions extraction
  • semi-supervised learning
  • local learning

Fingerprint Dive into the research topics of 'Protein-protein interactions classification from text via local learning with class priors'. Together they form a unique fingerprint.

  • Cite this

    He, Y., & Lin, C. (2009). Protein-protein interactions classification from text via local learning with class priors. In H. Horacek, E. Métais, R. Muñoz, & M. Wolska (Eds.), Natural language processing and information systems: 14th international conference on applications of natural language to information systems, NLDB 2009, Saarbrücken, Germany, June 24-26, 2009. Revised Papers (Vol. 5723, pp. 182-191). (Lecture notes in computer science; Vol. 5723). Springer. https://doi.org/10.1007/978-3-642-12550-8_15