Part of speech tagging with Na&amp;#x00EF;ve Bayes methods

Cretulescu, Radu George; David, Amos; Morariu, Daniel; Vintan, Lucian

doi:10.1109/icstcc.2014.6982457

Cited by 3 publications

(1 citation statement)

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“…For this purpose, using the Brown Corpus we have evaluated several known tagging (labeling the part of speech) applications and also some tagging applications which were developed by us [3], in order to find the best suited tagging application / applications for labeling the documents. The entire experiment for the Tagger selection was explained in our article published in [4].…”

Section: Tagging the Reuters Datasetmentioning

confidence: 99%

An Extension of the VSM Documents Representation

Vintan

Morariu

Cretulescu

et al. 2017

INT J COMPUT COMMUN

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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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Section: Tagging the Reuters Datasetmentioning

confidence: 99%