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BMCBI
2005
151views more  BMCBI 2005»
14 years 11 months ago
ProMiner: rule-based protein and gene entity recognition
Background: Identification of gene and protein names in biomedical text is a challenging task as the corresponding nomenclature has evolved over time. This has led to multiple syn...
Daniel Hanisch, Katrin Fundel, Heinz-Theodor Mevis...
WSDM
2010
ACM
266views Data Mining» more  WSDM 2010»
15 years 9 months ago
Gathering and Ranking Photos of Named Entities with High Precision, High Recall, and Diversity
Knowledge-sharing communities like Wikipedia and automated extraction methods like those of DBpedia enable the construction of large machine-processible knowledge bases with relat...
Bilyana Taneva, Mouna Kacimi, Gerhard Weikum
117
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AAAI
2007
15 years 2 months ago
Relation Extraction from Wikipedia Using Subtree Mining
The exponential growth and reliability of Wikipedia have made it a promising data source for intelligent systems. The first challenge of Wikipedia is to make the encyclopedia mac...
Dat P. T. Nguyen, Yutaka Matsuo, Mitsuru Ishizuka
CIKM
2005
Springer
15 years 5 months ago
A hybrid approach to NER by MEMM and manual rules
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
Moshe Fresko, Binyamin Rosenfeld, Ronen Feldman
LREC
2008
120views Education» more  LREC 2008»
15 years 1 months ago
Exploiting the Role of Position Feature in Chinese Relation Extraction
Relation extraction is the task of finding pre-defined semantic relations between two entities or entity mentions from text. Many methods, such as feature-based and kernel-based m...
Peng Zhang, Wenjie Li, Furu Wei, Qin Lu, Yuexian H...