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BMCBI
2005
251views more  BMCBI 2005»
13 years 7 months ago
Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
CIKM
2009
Springer
14 years 9 days ago
Probabilistic models for topic learning from images and captions in online biomedical literatures
Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and pro...
Xin Chen, Caimei Lu, Yuan An, Palakorn Achananupar...
IV
2007
IEEE
138views Visualization» more  IV 2007»
14 years 1 months ago
Visual Mashup of Text and Media Search Results
There is a growing trend of enabling users to view diverse sources of data in an integrated manner, called visual mashups. This paper addresses the problem of how to visualize div...
Anselm Spoerri
BMCBI
2008
173views more  BMCBI 2008»
13 years 7 months ago
Extraction of semantic biomedical relations from text using conditional random fields
Background: The increasing amount of published literature in biomedicine represents an immense source of knowledge, which can only efficiently be accessed by a new generation of a...
Markus Bundschus, Mathäus Dejori, Martin Stet...
IRCDL
2007
13 years 9 months ago
An Hybrid Approach for Improving Word Sense Disambiguation and Text Clustering
Abstract— In this paper we suggest a new approach to represent text document collections, integrating background knowledge to improve clustering effectiveness. Background knowled...
Paolo Casoto, Carlo Tasso