A BAYESIAN CLASSIFIER TO SEARCH AND CLASSIFY RESEARCH PAPERS

EDGAR ALAN CALVILLO MORENO; RICARDO MENDOZA GONZALEZ; JAIME MUÑOZ ARTEAGA; JULIO CESAR  MARTINEZ ROMO; MIGUEL VARGAS MARTIN; LAURA CECILIA RODRIGUEZ MARTINEZ

doi:https://doi.org/10.6036/NT7657

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A BAYESIAN CLASSIFIER TO SEARCH AND CLASSIFY RESEARCH PAPERS

JANUARY-DECEMBER 2015 - Volume: 2 - Pages: [14 p.]

DOI:

https://doi.org/10.6036/NT7657

Authors:

EDGAR ALAN CALVILLO MORENO -

RICARDO MENDOZA GONZALEZ

- JAIME MUÑOZ ARTEAGA -

JULIO CESAR MARTINEZ ROMO

- MIGUEL VARGAS MARTIN - LAURA CECILIA RODRIGUEZ MARTINEZ

Disciplines:

Computer Sciences (ARTIFICIAL INTELLIGENCE / INTELIGENCIA ARTIFICIAL )

Downloads: 130

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Received Date : 13 May 2015

Reviewing Date : 8 September 2015

Accepted Date : 13 September 2015

Key words:: Naive Bayes, Wrapper, Web-Searching, Knowledge DB, Search-Engine, Busqueda web, motor de búsqueda, Base datos de conocimiento
Article type:: ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:: RESEARCH ARTICLES

The objective of this paper was to provide an intelligent strategy to enhance web searching of scientific publications. The proposed approach helped to optimize web searching by applying a predictive Naive Bayes algorithm and automatic feeding of knowledge bases. The current sites took only information previously captured by the author of the paper in this information we could highlight title, abstract, key words, authors and a short description. In this work we provide an automatic feeding of knowledge bases to improve web searching of scientific publications and according to this we were able to provide an automatic feed of our knowledge database

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