Knowledge Discovery in Life Science Literature (eBook, PDF)

International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings
Redaktion: Bremer, Eric G.; Dubitzky, Werner; Berrar, Daniel; Han, Eui-Hong Sam; Hakenberg, Jörg

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 147
• Erscheinungstermin: 26. Februar 2006
• Englisch
• ISBN-13: 9783540328100
• Artikelnr.: 44224331

Autorenporträt

Eric G. Bremer, Children's Memorial Hospital, Chicago, IL, USA / Jörg Hakenberg, Humboldt-Universität zu Berlin, Germany / Eui-Hong Sam Han, iXmatch Inc., Minneapolis, MN, USA / Daniel Berrar, University of Ulster, Coleraine, Northern Ireland / Werner Dubitzky, University of Ulster, Coleraine, Northern Ireland

Inhaltsangabe

Alignment of Biomedical Ontologies Using Life Science Literature.- Improving Literature Preselection by Searching for Images.- Headwords and Suffixes in Biomedical Names.- A Tree Kernel-Based Method for Protein-Protein Interaction Mining from Biomedical Literature.- Recognizing Biomedical Named Entities Using SVMs: Improving Recognition Performance with a Minimal Set of Features.- Investigation of the Changes of Temporal Topic Profiles in Biomedical Literature.- Extracting Protein-Protein Interactions in Biomedical Literature Using an Existing Syntactic Parser.- Extracting Named Entities Using Support Vector Machines.- Extracting Initial and Reliable Negative Documents to Enhance Classification Performance.- Detecting Invalid Dictionary Entries for Biomedical Text Mining.- Automated Identification of Protein Classification and Detection of Annotation Errors in Protein Databases Using Statistical Approaches.- GetItFull - A Tool for Downloading and Pre-processing Full-Text Journal Articles.