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Ontology population for open‐source intelligence: A GATE‐based solution
Author(s) -
Ganino Giulio,
Lembo Domenico,
Mecella Massimo,
Scafoglieri Federico
Publication year - 2018
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2640
Subject(s) - computer science , ontology , pipeline (software) , realization (probability) , population , process (computing) , information retrieval , data science , field (mathematics) , workload , open source , world wide web , data mining , philosophy , statistics , epistemology , software , sociology , pure mathematics , programming language , operating system , demography , mathematics
Summary Open‐Source INTelligence is intelligence based on publicly available sources such as news sites, blogs, forums, etc. The Web is the primary source of information, but once data are crawled, they need to be interpreted and structured. Ontologies may play a crucial role in this process, but because of the vast amount of documents available, automatic mechanisms for their population are needed, starting from the crawled text. This paper presents an approach for the automatic population of predefined ontologies with data extracted from text and discusses the design and realization of a pipeline based on the General Architecture for Text Engineering system, which is interesting for both researchers and practitioners in the field. Some experimental results that are encouraging in terms of extracted correct instances of the ontology are also reported. Furthermore, the paper also describes an alternative approach and provides additional experiments for one of the phases of our pipeline, which requires the use of predefined dictionaries for relevant entities. Through such a variant, the manual workload required in this phase was reduced, still obtaining promising results.