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» Combining Candidate and Document Models for Expert Search
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TKDE
2010
224views more  TKDE 2010»
14 years 8 months ago
Probabilistic Topic Models for Learning Terminological Ontologies
—Probabilistic topic models were originally developed and utilised for document modeling and topic extraction in Information Retrieval. In this paper we describe a new approach f...
Wang Wei, Payam M. Barnaghi, Andrzej Bargiela
ICDAR
2003
IEEE
15 years 3 months ago
Symbolic Pruning in a Structural Approach to Engineering Drawing Analysis
Interpretation of paper drawings has received a good deal of attention over the last decade. Progress has also been made in related areas such as direct interpretation of human dr...
Tom Henderson, Lavanya Swaminatha
IRI
2007
IEEE
15 years 4 months ago
BESearch: A Supervised Learning Approach to Search for Molecular Event Participants
Biomedical researchers rely on keyword-based search engines to retrieve superficially relevant documents, from which they must filter out irrelevant information manually. Hence, t...
Richard Tzong-Han Tsai, Hong-Jie Dai, Hsi-Chuan Hu...
TCBB
2010
98views more  TCBB 2010»
14 years 4 months ago
VARUN: Discovering Extensible Motifs under Saturation Constraints
Abstract-The discovery of motifs in biosequences is frequently torn between the rigidity of the model on the one hand and the abundance of candidates on the other. In particular, m...
Alberto Apostolico, Matteo Comin, Laxmi Parida
CIKM
2006
Springer
15 years 1 months ago
Multi-evidence, multi-criteria, lazy associative document classification
We present a novel approach for classifying documents that combines different pieces of evidence (e.g., textual features of documents, links, and citations) transparently, through...
Adriano Veloso, Wagner Meira Jr., Marco Cristo, Ma...