Chinea Ríos, MaraSanchis Trilles, GermánCasacuberta Nolla, Francisco2016-05-192016-05-192015-06-09978-3-319-19389-20302-9743https://riunet.upv.es/handle/10251/64386The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19390-8_49In this paper, we present a clustering approach based on the combined use of a continuous vector space representation of sentences and the k-means algorithm. The principal motivation of this proposal is to split a big heterogeneous corpus into clusters of similar sentences. We use the word2vec toolkit for obtaining the representation of a given word as a continuous vector space. We provide empirical evidence for proving that the use of our technique can lead to better clusters, in terms of intra-cluster perplexity and F 1 score.Reserva de todos los derechosClusteringk-meansContinuous vector spacesLENGUAJES Y SISTEMAS INFORMATICOSCapítulo de libro10.1007/978-3-319-19390-8 49Abierto