Knowledge Discovery in Life Science Literature: International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings / Edition 1

Knowledge Discovery in Life Science Literature: International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings / Edition 1

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by Eric G. Bremer, Jorg Hakenberg, Eui-Hong Sam Han, Daniel Berrar, Werner Dubitzky
     
 

ISBN-10: 3540328092

ISBN-13: 9783540328094

Pub. Date: 05/05/2006

Publisher: Springer Berlin Heidelberg

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

Overview

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.

Product Details

ISBN-13:
9783540328094
Publisher:
Springer Berlin Heidelberg
Publication date:
05/05/2006
Series:
Lecture Notes in Computer Science / Lecture Notes in Bioinformatics Series , #3886
Edition description:
2006
Pages:
147
Product dimensions:
9.21(w) x 6.14(h) x 0.35(d)

Related Subjects

Table of Contents

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.

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