Neural network learning and expert systems
Neural network learning and expert systems
Entity-based cross-document coreferencing using the Vector Space Model
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A hierarchical naive Bayes mixture model for name disambiguation in author citations
Proceedings of the 2005 ACM symposium on Applied computing
Whither written language evaluation?
HLT '94 Proceedings of the workshop on Human Language Technology
Unsupervised personal name disambiguation
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Using a knowledge base to disambiguate personal name in web search results
Proceedings of the 2007 ACM symposium on Applied computing
Unsupervised relation disambiguation using spectral clustering
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Inferring Coreferences Among Person Names in a Large Corpus of News Collections
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
AUG: a combined classification and clustering approach for web people disambiguation
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
PSNUS: web people name disambiguation by simple clustering with rich features
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Shallow semantics for coreference resolution
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Name discrimination by clustering similar contexts
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
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In this paper we present a new algorithm for the Person Cross Document Coreference task. We show that accurate results require a way to adapt the parameters of the similarity function - metrics and threshold -- to the ontological constraints obeyed by individuals. The technique we propose dynamically changes the initial weights computed when the context is analyzed. The weight recomputation is necessary in order to resolve clusters borders, which are inevitably blurred by a static approach. The results show a significant gain in accuracy.