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Knowledge based approach to semantic composition of teams in an organization
Author(s) -
Simona Colucci,
Tommaso Di Noia,
Eugenio Di Sciascio,
Francesco M. Donini,
G. Piscitelli,
S. Coppi
Publication year - 2005
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-58113-964-0
DOI - 10.1145/1066677.1066974
Subject(s) - computer science , task (project management) , ontology , process (computing) , inference , composition (language) , selection (genetic algorithm) , exploit , description logic , semantic web , knowledge management , service composition , team composition , artificial intelligence , software engineering , information retrieval , natural language processing , web service , world wide web , programming language , philosophy , linguistics , computer security , management , epistemology , economics
Finding rapidly suitable experts in an organization to compose a team able to solve specific tasks is a typical problem in large consulting firms. In this paper we present a Description Logics approach to the semantic-based composition of ad-hoc teams based on individuals skill profiles and on task description. The selection process is carried out using a novel Concept Covering algorithm that exploits the recently proposed Concept Abduction inference service in Description Logics. The approach has been deployed as part of a skill management system that takes text files with curricula and project specifications as inputs and extracts from them available individual profiles and task descriptions, according to an ontology modeling skills.

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