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WSDM
2010
ACM
266views Data Mining» more  WSDM 2010»
14 years 2 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
LREC
2010
237views Education» more  LREC 2010»
13 years 7 months ago
Entity Mention Detection using a Combination of Redundancy-Driven Classifiers
We present an experimental framework for Entity Mention Detection in which two different classifiers are combined to exploit Data Redundancy attained through the annotation of a l...
Silvana Marianela Bernaola Biggio, Manuela Speranz...
CIKM
2005
Springer
13 years 11 months ago
Predicting accuracy of extracting information from unstructured text collections
Exploiting lexical and semantic relationships in large unstructured text collections can significantly enhance managing, integrating, and querying information locked in unstructur...
Eugene Agichtein, Silviu Cucerzan
LREC
2008
172views Education» more  LREC 2008»
13 years 7 months ago
CallSurf: Automatic Transcription, Indexing and Structuration of Call Center Conversational Speech for Knowledge Extraction and
Being the client's first interface, call centres worldwide contain a huge amount of information of all kind under the form of conversational speech. If accessible, this infor...
Martine Garnier-Rizet, Gilles Adda, Frederik Caill...
BMCBI
2008
153views more  BMCBI 2008»
13 years 5 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, ...