Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Entity-based cross-document coreferencing using the Vector Space Model
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Disambiguating Web appearances of people in a social network
WWW '05 Proceedings of the 14th international conference on World Wide Web
Coreference for NLP applications
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Person resolution in person search results: WebHawk
Proceedings of the 14th ACM international conference on Information and knowledge management
Unsupervised personal name disambiguation
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Person name disambiguation in web pages using social network, compound words and latent topics
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
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We are developing a reference disambiguation system called NAYOSE System. In order to cope with the case the same person name or place name appears over two or more Web pages, we propose a system classifying each page into a cluster which corresponds to the same entity in the real world. For this purpose, we propose two new methods involving algorithms to classify these pages. In our evaluation, the combination of local text matching and named entities matching outperformed the previous baseline algorithm used in simple document classification method by 0.22 in the overall F-measure.