Cross-lingual event-centered news clustering aims to perform the clustering of news documents written in different languages into groups of documents that describe the same event. In order to solve the problem of similarity computation between bi-lingual documents, this paper propose a new method based on semantic correlations of news elements. First, using bilingual entity lexical and terms co-occurrences in news to acquire the semantic correlation of news elements in different language. Then, we compute the similarity between news in different languages using the GVSM model on this basis. Finally, Spectral Clustering is applied to categorize news stories. Experimental results show our method achieves promising results on the F value.
Multimedia Tools and Applications – Springer Journals
Published: Jul 7, 2017
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