Conceptual Map Creation from Natural Language Processing: a Systematic Mapping Study
DOI:
https://doi.org/10.5753/rbie.2019.27.03.150Keywords:
Concept Map, Natural Language Processing, Knowledge Representation, Systematic Mapping StudyAbstract
Context: Conceptual Maps (CMs) have been used to organize knowledge and facilitate learning and teaching in multiple domains. CMs are also used in multiple settings in education, since they are able to clarify the relationships between the subcomponents of a particular topic. However, the construction of a CM requires time and effort in identifying and structuring knowledge. In order to mitigate this problem, Natural Language Processing (NLP) techniques have been employed and have contributed to automate the extraction of concepts and relationships from texts. Objective: This article summarizes the main initiatives of building CMs from NLP. Method: A systematic mapping study was used to identify primary studies that present approaches on the use of NLP to automatically create CMs. Results: The mapping provides a description of 23 available articles that have been reviewed in order to extract relevant information on a set of Research Questions (RQ). From the answers to RQ, a classification scheme was designed in order to present how NLP could be employed to construct CMs. From this classification scheme, a graph was elaborated to present different paths to construct CMs using NLP. Conclusions: The construction of CMs using NLP is still a recent topic, however, it has been proven to be effective in assisting the automatic construction of CMs.
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Copyright (c) 2019 Vinicius dos Santos, Érica Ferreira de Souza, Katia Romero Felizardo, Willian Massami Watanabe, Nandamudi L. Vijaykumar, Sandra Maria Aluizio, Arnaldo Candido
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
