Entity-based cross-document coreferencing using the Vector Space Model
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Unsupervised personal name disambiguation
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
SenseClusters - finding clusters that represent word senses
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
The SemEval-2007 WePS evaluation: establishing a benchmark for the web people search task
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UMCC-DLSI: Integrative resource for disambiguation task
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Person name discrimination in the dossier-GPLSI at the university of Alicante
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Hi-index | 0.00 |
This paper presents an approach for web page clustering. The different underlying meanings of a name are discovered on the basis of the title of the web page, the body content, the common named entities across the documents and the sub-links. This information is feeded into a K-Means clustering algorithm which groups together the web pages that refer to the same individual.