Abstract
The large amounts and growing of unstructured texts, available in Internet and other scenarios, are becoming a very valuable resource of information and knowledge. The present work describes a concept-based text analysis approach, based on the use of a knowledge graph for structuring the texts content and a query language for retrieving relevant information and obtaining knowledge from the knowledge graph automatically generated. In the querying process, a semantic analysis method is applied for searching and integrating the conceptual structures from the knowledge graph, which is supported by a disambiguation algorithm and WordNet. The applicability of the proposed approach was evaluated in the analysis of scientific articles from a Systematic Literature Review and the results were contrasted with the conclusions obtained by the authors of this review.
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This work has been partially supported by FEDER and the State Research Agency (AEI) of the Spanish Ministry of Economy and Competition under grant MERINET: TIN2016-76843-C4-2-R (AEI/FEDER, UE)
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Hojas-Mazo, W., Simón-Cuevas, A., de la Iglesia Campos, M., Romero, F.P., Olivas, J.A. (2018). A Concept-Based Text Analysis Approach Using Knowledge Graph. In: Medina, J., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 854. Springer, Cham. https://doi.org/10.1007/978-3-319-91476-3_57
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