Sentence Clustering Using Continuous Vector Space Representation
نویسندگان
چکیده
In 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 F1 score.
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