Acquisition of Terminological Knowledge from Social Networks in Description Logic

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in Buch/Sammelband/GutachtenBeigetragenBegutachtung

Abstract

The Web Ontology Language (OWL) has gained serious attraction since its foundation in 2004, and it is heavily used in applications requiring representation of as well as reasoning with knowledge. It is the language of the Semantic Web, and it has a strong logical underpinning by means of so-called Description Logics (DLs). DLs are a family of conceptual languages suitable for knowledge representation and reasoning due to their strong logical foundation, and for which the decidability and complexity of common reasoning problems are widely explored. In particular, the reasoning tasks allow for the deduction of implicit knowledge from explicitly stated facts and axioms, and plenty of appropriate algorithms were developed, optimized, and implemented, e.g., tableaux algorithms and completion algorithms. In this document, we present a technique for the acquisition of terminological knowledge from social networks. More specifically, we show how OWL axioms, i.e., concept inclusions and role inclusions in DLs, can be obtained from social graphs in a sound and complete manner. A social graph is simply a directed graph, the vertices of which describe the entities, e.g., persons, events, messages, etc.; and the edges of which describe the relationships between the entities, e.g., friendship between persons, attendance of a person to an event, a person liking a message, etc. Furthermore, the vertices of social graphs are labeled, e.g., to describe properties of the entities, and also the edges are labeled to specify the concrete relationships. As an exemplary social network we consider Facebook, and show that it fits our use case.

Details

OriginalspracheEnglisch
TitelFormal Concept Analysis of Social Networks
Redakteure/-innenRokia Missaoui, Sergei O. Kuznetsov, Sergei Obiedkov
ErscheinungsortCham
Herausgeber (Verlag)Springer International Publishing AG
Seiten97-142
Seitenumfang46
PublikationsstatusVeröffentlicht - 4 Nov. 2017
Peer-Review-StatusJa

Publikationsreihe

ReiheLecture notes in social networks : (LNSN)

Externe IDs

ORCID /0000-0003-0219-0330/work/153109394