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Concept Identification from Single-Documents

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Technologies and Innovation (CITI 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 883))

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Abstract

This article presents a method that extracts relevant concepts automatically, consisting of one or several words, whose main contribution is that it does so from a single document of any domain, regardless of its length; however, documents of short length are used (which are the most frequent to obtain on the web) to perform the work. This research was conducted for documents written in Spanish and was tested in multiple randomized domains to compare their results. For this, an algorithm was used to automatically identify syntactic patterns in the document. This work uses the previous work of [1] to obtain its results. This algorithm is based on statistical approximations and on the length of the identifiable patterns contained in the document, applies certain heuristic that can enhance or decrease the patterns’ choice according to the selection of one of the 5 methods that are processed (M1 to M5), with these patterns the candidate concepts are obtained, which go through another evaluation process that will obtain the final concepts. This proposal presents at least four advantages: (1) It is multi-domain, (2) It is independent of the text length, (3) It can work with one or more documents and (4) It allows the discarding of garbage or undesirable patterns from the beginning. The method was implemented in 11 different domains and its results range varies between 58%–70% of precision and 25%–46% of recall.

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Notes

  1. 1.

    http://www.lsi.upc.es/~nlp/tools/parole-sp.html.

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Authors and Affiliations

  1. Department of Industrial Engineering, Universidad de Sonora, Blvd. Rosales y Transversal, 83000, Hermosillo, Sonora, Mexico

    José Luis Ochoa-Hernández, Mario Barcelo-Valenzuela, Gerardo Sanchez-Smitz & Raquel Torres-Peralta

Authors
  1. José Luis Ochoa-Hernández
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  2. Mario Barcelo-Valenzuela
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  3. Gerardo Sanchez-Smitz
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  4. Raquel Torres-Peralta
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Corresponding author

Correspondence to José Luis Ochoa-Hernández .

Editor information

Editors and Affiliations

  1. Facultad de Informática, Universidad de Murcia, Murcia, Spain

    Rafael Valencia-García

  2. Departamento de Filología Moderna, Universidad de Castilla la Mancha, Ciudad Real, Ciudad Real, Spain

    Gema Alcaraz-Mármol

  3. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Javier Del Cioppo-Morstadt

  4. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Néstor Vera-Lucio

  5. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Martha Bucaram-Leverone

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Ochoa-Hernández, J.L., Barcelo-Valenzuela, M., Sanchez-Smitz, G., Torres-Peralta, R. (2018). Concept Identification from Single-Documents. In: Valencia-García, R., Alcaraz-Mármol, G., Del Cioppo-Morstadt, J., Vera-Lucio, N., Bucaram-Leverone, M. (eds) Technologies and Innovation. CITI 2018. Communications in Computer and Information Science, vol 883. Springer, Cham. https://doi.org/10.1007/978-3-030-00940-3_12

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  • DOI: https://doi.org/10.1007/978-3-030-00940-3_12

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