An Extension of the VSM Documents Representation

  • Lucian Nicolae Vintan "Lucian Blaga" University Sibiu
  • Daniel Ionel Morariu "Lucian Blaga" University Sibiu
  • Radu George Cretulescu "Lucian Blaga" University Sibiu
  • Maria Vintan "Lucian Blaga" University Sibiu


In this paper we will present a new approach regarding the documents representation in order to be used in classification and/or clustering algorithms. In our new representation we will start from the classical "bag-of-words" representation but we will augment each word with its correspondent part-of-speech. Thus we will introduce a new concept called hyper-vectors where each document is represented in a hyper-space where each dimension is a different part-of-speech component. For each dimension the document is represented using the Vector Space Model (VSM). In this work we will use only five different parts of speech: noun, verb, adverb, adjective and others. In the hyper-space each dimension has a different weight. To compute the similarity between two documents we have developed a new hyper-cosine formula. Some interesting classification experiments are presented as validation cases.


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How to Cite
VINTAN, Lucian Nicolae et al. An Extension of the VSM Documents Representation. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 12, n. 3, p. 402-414, apr. 2017. ISSN 1841-9844. Available at: <>. Date accessed: 27 sep. 2020. doi:


documents representation, vector space model, hyper-vectors, documents similarity, classification, clustering