Abstract

In this paper, we propose a novel method that performs Cross Language Text Categorization (CLTC) from the perspective of Information Retrieval. We present an input document in target language in the form of a query in source language. Then we retrieve the training documents in source language and find K most relevant results. At last, we use the class labels of the K results to predict the class of the input document. The only external resource required by our method is a bilingual dictionary. Experimental results show that our method gives promising performance, which is better than translation-based method.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.