Browsing by Author "Sumba Toral, Francisco Xavier"

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Author-topic classification based on semantic knowledge
(Springer Verlag, 2019) Segarra Flores, José Luis; Sumba Toral, Francisco Xavier; Ortiz Vivar, Jose Enrique; Gualan Saavedra, Ronald Marcelo; Espinoza Mejía, Jorge Mauricio; Saquicela Galarza, Víctor Hugo
We propose a novel unsupervised two-phased classification model leveraging from semantic web technologies for discovering common research fields between researchers based on information available from a bibliographic repository and external resources. The first phase performs coarse-grained classification by knowledge disciplines using as reference the disciplines defined in the UNESCO thesaurus. The second phase provides a fine-grained classification by means of a clustering approach combined with external resources. The methodology was applied to the REDI (Semantic Repository of Ecuadorian researchers) project, with remarkable results and thus proving a valuable tool to one of the main REDI’s goals discover Ecuadorian authors sharing research interests to foster collaborative research efforts.
Detecting similar areas of knowledge using semantic and data mining technologies
(2016) Sumba Orellana, Freddy Fernando; Sumba Toral, Francisco Xavier; Saquicela Galarza, Víctor Hugo
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.
REDI: a linked data-powered research networking platform
(Springer, 2018) Sumba Toral, Francisco Xavier; Segarra Flores, José Luis; Villazón Terrazas, Boris Marcelo; Espinoza Mejía, Jorge Mauricio; Saquicela Galarza, Víctor Hugo; Sumba Toral, Francisco Xavier
Research networking is a difficult part of academics in spite of the multiple benefits that the Web has brought within this field in recent years. Even though scientific and business social networks provide a medium to discover peers worldwide, their usefulness meets its limits when real-world requirements come in. The broad audience of those tools and other bibliographic databases lead them to ignore cultural and geographical aspects such regional indexes, organizational structures, among others. On this poster, we introduce REDI, a Linked Data - powered research networking platform which combines both local (institutional/regional) and external (Web) scholarly sources in a consolidated knowledge base. Moreover, REDI leverages on its knowledge base to cluster authors within similar research areas easing networking and unveiling a variety of new information from data for multiple purposes.
Semantically identifying regional-indexed publications, a web-exploring approach
(IEEE, 2018) Ortiz Vivar, Jose Enrique; Sumba Toral, Francisco Xavier; Segarra Flores, Jose Luis; Saquicela Galarza, Víctor Hugo
The indexing services are an important element of researching process because they make publicly available research results and articles for the community. Furthermore, regional indices such Latindex have contributed to spreading scientific works and incentivizing research in the Latin-American context. However, the un-centralized publication approach that its member journals follow has made impossible to form a unified view of Latindex-indexed articles and its corresponding journals. This drawback has limited activities such biblio-metric studies and integration from the perspective of information systems. In this paper, a linking mechanism between journals and publications is outlined, which aims to identify explicitly whether or not an arbitrary article belongs to Latindex. The proposed approach leverages on the Linked Data principles and takes advantage of web search engines to validate its results. This proposal has successfully been evaluated on an Ecuadorian publications dataset obtaining a 0.91 f-score respect to a manually classified sample. © 2018 IEEE.