Cross-Lingual Document Similarity Calculation Using the Multilingual Thesaurus EUROVOC
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Experiments with the Eurospider Retrieval System for CLEF 2001
CLEF '01 Revised Papers from the Second Workshop of the Cross-Language Evaluation Forum on Evaluation of Cross-Language Information Retrieval Systems
A multilingual news summarizer
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Multilingual document clustering: an heuristic approach based on cognate named entities
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Multilingual and cross-lingual news topic tracking
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Cross language text categorization by acquiring multilingual domain models from comparable corpora
ParaText '05 Proceedings of the ACL Workshop on Building and Using Parallel Texts
A neural network model for hierarchical multilingual text categorization
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
On fuzzy logic applications for automatic control, supervision, and fault diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Fuzzy Systems
Finding news story chains based on multi-dimensional event profiles
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
Discovering links between political debates and media
ICWE'13 Proceedings of the 13th international conference on Web Engineering
| Hi-index | 0.00 |
This paper is focused on discovering bilingual news clusters in a comparable corpus. Particularly, we deal with the news representation and with the calculation of the similarity between documents. We use as representative features of the news the cognate named entities they contain. One of our main goals consists of proving whether the use of only named entities is a good source of knowledge for multilingual news clustering. In the vectorial news representation we take into account the category of the named entities. In order to determine the similarity between two documents, we propose a new approach based on a fuzzy system, with a knowledge base that tries to incorporate the human knowledge about the importance of the named entities category in the news. We have compared our approach with a traditional one obtaining better results in a comparable corpus with news in Spanish and English.