Abstract. This article deals with the problem of Cross-Lingual Text Categorization (CLTC), which arises when documents in different languages must be classified according to the same classification tree. We describe practical and cost-effective solutions for automatic Cross-Lingual Text Categorization, both in case a sufficient number of training examples is available for each new language and in the case that for some language no training examples are available. Experimental results of the bi-lingual classification of the ILO corpus (with documents in English and Spanish) are obtained using bi-lingual training, terminology translation and profile-based translation.
With the globalization trend there is a big amount of documents writ- ten in different languages. If...
Abstract. In this paper, we investigate strategies for automatically classifying documents in differ...
This paper deals with various methods for multilingual document categorization and informs about the...
This article deals with the problem of Cross-Lingual Text Categorization (CLTC), which arises when d...
This article addresses the question of how to deal with text categorization when the set of document...
Cross-language Text Categorization is the task of assigning semantic classes to documents written i...
Due to the globalization on the Web, many companies and institutions need to efficiently organize an...
In a multilingual scenario, the classical monolingual text categorization problem can be reformulate...
Due to the globalization on the Web, many companies and institutions need to efficiently organize an...
Abstract. With the rapid emergence and proliferation of Internet and the trend of globalization, a t...
The patent describes a method and a system for generating classifiers from multilingual corpora incl...
Most enterprise search engines employ data mining classifiers to classify documents. Along with the ...
Cross language classification is an important task in multilingual learning, where documents in diff...
Most enterprise search engines employ data mining classifiers to classify documents. Along with the ...
We address the problem of learning text categorization from a corpus of multilingual documents. We p...
With the globalization trend there is a big amount of documents writ- ten in different languages. If...
Abstract. In this paper, we investigate strategies for automatically classifying documents in differ...
This paper deals with various methods for multilingual document categorization and informs about the...
This article deals with the problem of Cross-Lingual Text Categorization (CLTC), which arises when d...
This article addresses the question of how to deal with text categorization when the set of document...
Cross-language Text Categorization is the task of assigning semantic classes to documents written i...
Due to the globalization on the Web, many companies and institutions need to efficiently organize an...
In a multilingual scenario, the classical monolingual text categorization problem can be reformulate...
Due to the globalization on the Web, many companies and institutions need to efficiently organize an...
Abstract. With the rapid emergence and proliferation of Internet and the trend of globalization, a t...
The patent describes a method and a system for generating classifiers from multilingual corpora incl...
Most enterprise search engines employ data mining classifiers to classify documents. Along with the ...
Cross language classification is an important task in multilingual learning, where documents in diff...
Most enterprise search engines employ data mining classifiers to classify documents. Along with the ...
We address the problem of learning text categorization from a corpus of multilingual documents. We p...
With the globalization trend there is a big amount of documents writ- ten in different languages. If...
Abstract. In this paper, we investigate strategies for automatically classifying documents in differ...
This paper deals with various methods for multilingual document categorization and informs about the...