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Smart Data Integration by Goal Driven Ontology Learning

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Advances in Big Data (INNS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 529))

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Abstract

The smart data integration approach is proposed to compose data and knowledge of the different nature, origin, formats and standards. This approach is based on the selective goal driven ontology learning. The automated planning paradigm in a combination with a value of the perfect information approach is proposed to be used for evaluating the knowledge correspondence with the learning goal for the data integration domain. The information model of a document is represented as a supplement to the Partially Observable Markov Decision Process (POMDP) strategy of a domain. It helps to estimate the document a pertinence as the increment of the strategy expected utility. A statistical method for identifying the semantic relations in the natural language texts for their linguistic characteristics is developed. It helps to extract the Ontology Web Language (OWL) predicates from the natural language text using data about sub semantic links. A set of methods and means based on ontology learning was developed to support the smart data integration process. A technology uses the Natural Language Processing software Link Grammar Parser, WordNet Application Programming Interface (API) as well as the OWL API.

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Acknowledgments

This work is supported by China 973 fundamental research and development project, grant number 2014CB340404; the National Natural Science Foundation of China, grant number 61373037.

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Authors and Affiliations

  1. State Key Lab of Software Engineering, Computer School, Wuhan University, Wuhan, China

    Jingliang Chen

  2. Computer School, Hubei University of Technology, Wuhan, China

    Jingliang Chen

  3. Lviv National Polytechnic University, 12 Bandery Street, Lviv, 79013, Ukraine

    Dmytro Dosyn & Vasyl Lytvyn

  4. Silesian University of Technology, ul. Roosevelta 26-28, 41-800, Zabrze, Poland

    Anatoliy Sachenko

  5. Ternopil National Economic University, 3 Peremogy Square, Ternopil, 46020, Ukraine

    Anatoliy Sachenko

Authors
  1. Jingliang Chen
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  2. Dmytro Dosyn
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  3. Vasyl Lytvyn
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  4. Anatoliy Sachenko
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Corresponding author

Correspondence to Anatoliy Sachenko .

Editor information

Editors and Affiliations

  1. School of Computing and Communications, Lancaster University , Lancaster, United Kingdom

    Plamen Angelov

  2. Data Engineering Lab, Dept. of Informatics, Aristotle University of Thessaloniki , Thessaloniki, Greece

    Yannis Manolopoulos

  3. Lab of Forest Informatics (FiLAB), Democritus University of Thrace , Orestiada, Greece

    Lazaros Iliadis

  4. WPC Information Systems Faculty, Arizona State University , Tempe, Arizona, USA

    Asim Roy

  5. Electrical Engineering Dept, (ICA), Pontifical Catholic Univ of Rio de Janei , Rio de Janeiro, Rio de Janeiro, Brazil

    Marley Vellasco

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Chen, J., Dosyn, D., Lytvyn, V., Sachenko, A. (2017). Smart Data Integration by Goal Driven Ontology Learning. In: Angelov, P., Manolopoulos, Y., Iliadis, L., Roy, A., Vellasco, M. (eds) Advances in Big Data. INNS 2016. Advances in Intelligent Systems and Computing, vol 529. Springer, Cham. https://doi.org/10.1007/978-3-319-47898-2_29

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  • DOI: https://doi.org/10.1007/978-3-319-47898-2_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47897-5

  • Online ISBN: 978-3-319-47898-2

  • eBook Packages: EngineeringEngineering (R0)

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