Competence Mining for Collaborative Virtual Enterprise

Abstract

Abstract. In a context of decision-aid to support the identification of collaborative networks, this paper focuses on extracting essential facets of firm competencies. We present an approach for enrichment of competence ontology, based on two steps where a novel effective filtering step is utilized. First we extract the correlation between terms of a learning dataset using the generation of association rules. Second we retain the relevant new concepts using an extracted semantic information. The suggested approach was tested on an ontology of mechanical industry competencies. Experiments were performed on real data, which show the usefulness of our approach.

(Playing) Government beyond Pen & Paper: Conceptualization, Implementation, and Outlook

“…The game proposed by [6] as-is provides a strategy to teach a set of commonly accepted competences-however, so far it cannot detect and respond to a participant group's current state of competences. Since the presented platform will provide us with at least semi-structured data from the participants, we see the potential to connect back to attempts to inductively mine competences from textual data as proposed by [18,19]. These insights can then be used to identify areas where participants need additional feedback or training, as well as to unveil pathways to create additional simulation games tailored to specific participant profiles.…”

“…However, studies related to other settings found that SGs contribute to a good learning result [14,15], which can especially be gained through the use of interaction platforms [16]. Exemplary cases for the implementation of a simulation game platform are already available for the BPM area [17] but not yet designed for the area of eGovernment and not recognizing the possibility to evaluate the current competences of partaking learners via application of competence mining [18][19][20].…”

The Network Structure of Visited Locations According to Geotagged Social Media Photos

“…The complex structure of actors and their relations is particularly relevant in socioeconomic systems. This has triggered a long history of interdisciplinary collaboration between network science and fields such as computational sociology [10], transportation systems [7], [11], economy [12], and also that of collaborative networks, which is increasingly benefiting from data-driven approaches [13], [14].…”