A Domain-Adaptable Heterogeneous Information Integration Platform: Tourism and Biomedicine Domains

• Published in: Information (Basel) Vol. 12; no. 11; p. 435
• Main Authors: Gil, Rafael Muñoz, de Buenaga Rodríguez, Manuel, Galisteo, Fernando Aparicio, Páez, Diego Gachet, García-Cuesta, Esteban
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2021
• Subjects: Domains; information fusion; Information sources; Information systems; intelligent agents; Modularity; Natural language processing; New technology; Performance measurement; recommenders; Semantic Web; Social networks; Standardization; Tourism
• ISSN: 2078-2489; 2078-2489
• DOI: 10.3390/info12110435

In recent years, information integration systems have become very popular in mashup-type applications. Information sources are normally presented in an individual and unrelated fashion, and the development of new technologies to reduce the negative effects of information dispersion is needed. A major challenge is the integration and implementation of processing pipelines using different technologies promoting the emergence of advanced architectures capable of processing such a number of diverse sources. This paper describes a semantic domain-adaptable platform to integrate those sources and provide high-level functionalities, such as recommendations, shallow and deep natural language processing, text enrichment, and ontology standardization. Our proposed intelligent domain-adaptable platform (IDAP) has been implemented and tested in the tourism and biomedicine domains to demonstrate the adaptability, flexibility, modularity, and utility of the platform. Questionnaires, performance metrics, and A/B control groups’ evaluations have shown improvements when using IDAP in learning environments.