Detecting Similar Areas of Knowledge Using Semantic and Data Mining Technologies
Xavier Sumba, Freddy Sumba, Andrés Tello, Fernando Baculima, Mauricio J. Espinoza, Víctor Saquicela · Electronic Notes in Theoretical Computer Science · 2016
Searching for scientific publications online is an essential task for researchers working on a certain topic. However, the extremely large amount of scientific publications found in the web turns the process of finding a publication into a very difficult task whereas, locating peers interested in collaborating on a specific topic or reviewing literature is even more challenging. In this paper, we propose a novel architecture to join multiple bibliographic sources, with the aim of identifying common research areas and potential collaboration networks, through a combination of ontologies, vocabularies, and Linked Data technologies for enriching a base data model. Furthermore, we implement a prototype to provide a centralized repository with bibliographic sources and to find similar knowledge areas using data mining techniques in the domain of Ecuadorian researchers community.