Conference Paper

Efficient Automatic Selection of Semantically-Annotated Building Blocks for ERPs Customizing

DOI: 10.1007/978-3-540-72035-5_18 Conference: Business Information Systems, 10th International Conference, BIS 2007, Poznan, Poland, April 25-27, 2007, Proceedings
Source: DBLP


We present an approach for efficient semantic-based building-blocks selection in the context of ERPs fast customizing, introducing
Enduring Oak, a framework that implements an optimized greedy concept covering algorithm, able to deal with thousands of building
block descriptions with reasonable computational times. The proposed approach uses a Description Logics reasoning engine in
conjunction with a RDBMS to reduce the computational burden. We motivate the approach, present the framework and algorithms
and illustrate experiments confirming the validity of our setting.

Download full-text


Available from: Tommaso Di Noia, Sep 30, 2015
11 Reads
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Proceedings of the 2005 ACM Symposium on Applied Computing (SAC), Santa Fe, New Mexico, USA, March 13-17, 2005; 03/2005
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery.
    Journal of Artificial Intelligence Research 05/2007; 29:269-307. DOI:10.1613/jair.2153 · 1.26 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article presents such a solution, namely KAON SERVER, an on-going project intended to provide a transactional, multi-user-capable and secure Semantic Web management system
Show more