Sciweavers

61 search results - page 10 / 13
» Name Tagging with Word Clusters and Discriminative Training
Sort
View
BMCBI
2004
104views more  BMCBI 2004»
13 years 6 months ago
Discriminative topological features reveal biological network mechanisms
Background: Recent genomic and bioinformatic advances have motivated the development of numerous network models intending to describe graphs of biological, technological, and soci...
Manuel Middendorf, Etay Ziv, Carter Adams, Jen Hom...
IJCNN
2006
IEEE
14 years 22 days ago
A Self-Organising Map Approach for Clustering of XML Documents
— The number of XML documents produced and available on the Internet is steadily increasing. It is thus important to devise automatic procedures to extract useful information fro...
Francesca Trentini, Markus Hagenbuchner, Alessandr...
BMCBI
2008
153views more  BMCBI 2008»
13 years 6 months ago
How to make the most of NE dictionaries in statistical NER
Background: When term ambiguity and variability are very high, dictionary-based Named Entity Recognition (NER) is not an ideal solution even though large-scale terminological reso...
Yutaka Sasaki, Yoshimasa Tsuruoka, John McNaught, ...
JUCS
2007
84views more  JUCS 2007»
13 years 6 months ago
Improving the Performance of a Tagger Generator in an Information Extraction Application
: In this paper we present an experience in the extraction of named entities from Spanish texts using stacking. Named Entity Extraction (NEE) is a subtask of Information Extraction...
José A. Troyano, Fernando Enríquez, ...
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
14 years 1 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...