Author-Topic Classification Based on Semantic Knowledge

Segarra, José Ignacio Ortíz; Sumba, Xavier; Ortíz, José; Gualán, Ronald; Mejía, Mauricio Espinoza; Saquicela, Víctor

doi:10.1007/978-3-030-21395-4_5

Cited by 3 publications

(1 citation statement)

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“…The information of both clusters and subclusters is converted to RDF using the Simple Knowledge Organization System (SKOS) ontology [26]. The complete workflow and algorithms used in this classification process are explained in more detail in Segarra et al [27] Figure 2. UNESCO semantic clustering.…”

Section: Collaboration Networkmentioning

confidence: 99%

REDI: Towards knowledge graph-powered scholarly information management and research networking

Vivar

Segarra

Villazón-Terrazas

et al. 2020

Journal of Information Science

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Academic data management has become an increasingly challenging task as research evolves over time. Essential tasks such as information retrieval and research networking have turned into extremely difficult operations due to an ever-growing number of researchers and scientific articles. Numerous initiatives have emerged in the IT environments to address this issue, especially focused on web technologies. Although those approaches have individually provided solutions for diverse problems, they still can not offer integrated knowledge bases nor flexibility to exploit adequately this information. In this article, we present REDI, a Linked Data-powered framework for academic knowledge management and research networking, which introduces a new perspective of integration. REDI combines information from multiple sources into a consolidated knowledge base through state-of-the-art procedures and leverages semantic web standards to represent the information. Moreover, REDI takes advantage of such knowledge for data visualisation and analysis, which ultimately improves and simplifies many activities including research networking.

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Section: Collaboration Networkmentioning

confidence: 99%