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BMCBI
2005
151views more  BMCBI 2005»
14 years 9 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 7 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
AAAI
2007
14 years 12 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 3 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»
14 years 11 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...