Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
An Engineering Approach for the Design of Hybrid Modelling Methods Kapitel lesen Erstes Kapitel lesen

2013 | OriginalPaper | Buchkapitel

Finding Semi-Automatically a Greatest Common Model Thanks to Formal Concept Analysis

verfasst von : Bastien Amar, Abdoulkader Osman Guédi, André Miralles, Marianne Huchard, Thérèse Libourel, Clémentine Nebut

Erschienen in: Enterprise Information Systems

Verlag: Springer Berlin Heidelberg

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Data integration and knowledge capitalization combine data and information coming from different data sources designed by different experts having different purposes. In this paper, we propose to assist the underlying model merging activity. For close models made by experts of various specialities on the same system, we partially automate the identification of a Greatest Common Model (GCM) which is composed of the common concepts (core-concepts) of the different models. Our methodology is based on Formal Concept Analysis which is a method of data analysis based on lattice theory. A decision tree allows to semi-automatically classify concepts from the concept lattices and assist the GCM extraction. We apply our approach on the EIS-Pesticide project, an environmental information system which aims at centralizing knowledge and information produced by different research teams.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Social Information Systems: Agility Without Chaos
Nächstes Kapitel Advanced Product Lifecycle Management by Introducing Domain-Specific Service Buses
Fußnoten
1
This article is an extension of Using Formal Concept Analysis to Extract a Greatest Common Model published in the ICEIS 2012 conference.
 
2
Here, we refer to the relational normal form used in database schema normalization, which has the same objective: eliminate redundancies.
 
3
In the literature, standard notation is \(K = (G, M, I)\). We use \(K = (E, C, R)\) for readability reasons and to get a better understanding toward our thematic partners.
 
4
http://​www.​objecteering.​com/​. The development has been done with Objecteering but we are migrating it to Modelio, the last version of Objecteering.
 
6
In these tables, new and merged concepts must be still validated by an expert.
 
Literatur
1.
Pinet, F., Miralles, A., Bimonte, S., Vernier, F., Carluer, N., Gouy, V., Bernard, S.: The use of uml to design agricultural data warehouses. In: International Conference on Agricultural Engineering (AgEng 2010), pp. 1–10 (2010)
2.
Miralles, A., Pinet, F., Carluer, N., Vernier, F., Bimonte, S., Lauvernet, C., Gouy, V.: EIS-Pesticide: an information system for data and knowledge capitalization and analysis. In: Euraqua-PEER Scientific Conference 1, 26 Oct 2011–28 Oct 2011, Montpellier, FRA (2011)
3.
Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundation. Springer, Berlin (1999)CrossRef
4.
Birkhoff, G.: Lattice theory. American Mathematical Society, Providence (1940)
5.
Osman Guedi, A., Miralles, A., Huchard, M., Nebut, C.: Analyse de l’évolution d’un modèle : vers une méthode basée sur l’analyse formelle de concepts. In: XXIXème Congrès INFORSID (2011)
6.
Falleri, J.R.: Contributions à l’IDM : reconstruction et alignement de modèles de classes. Ph.D. thesis, Université Montpellier 2 (2009)
7.
Rouane, M.H., Dao, M., Huchard, M., Valtchev, P.: Aspects de la réinginierie des modèles uml par analyse de données relationnelles. Ingénierie des Systèmes d’information (RSTI série) 12, 39–68 (2007)CrossRef
8.
Godin, R., Mili, H.: Building and maintaining analysis-level class hierarchies using galois lattices. In: Eighth Annual Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA), pp. 394–410 (1993)
9.
Dao, M., Huchard, M., Hacene, M.R., Roume, C., Valtchev, P.: Towards practical tools for mining abstractions in uml models. In: International Conference on Enterprise Information Systems: Databases and Information Systems Integration (ICEIS 2006), pp. 276–283 (2006)
10.
Arévalo, G., Falleri, J.-R., Huchard, M., Nebut, C.: Building abstractions in class models: Formal concept analysis in a model-driven approach. In: Wang, J., Whittle, J., Harel, D., Reggio, G. (eds.) MoDELS 2006. LNCS, vol. 4199, pp. 513–527. Springer, Heidelberg (2006)
11.
Altmanninger, K., Seidl, M., Wimmer, M.: A survey on model versioning approaches. Int. J. Web Inf. Syst. 5, 271–304 (2009)CrossRef
12.
Altmanninger, K., Schwinger, W., Kotsis, G.: Semantics for accurate conflict detection in smover: Specification, detection and presentation by example. Int. J. Enterp. Inf. Syst. 6, 68–84 (2010)CrossRef
13.
Cicchetti, A., Di Ruscio, D., Pierantonio, A.: Managing model conflicts in distributed development. In: Czarnecki, K., Ober, I., Bruel, J.-M., Uhl, A., Völter, M. (eds.) MODELS 2008. LNCS, vol. 5301, pp. 311–325. Springer, Heidelberg (2008)
14.
Cicchetti, A., Ruscio, D.D., Pierantonio, A.: A metamodel independent approach to difference representation. J. Object Technol. 6, 165–185 (2007)CrossRef
15.
Ohst, D., Welle, M., Kelter, U.: Differences between versions of uml diagrams. SIGSOFT Softw. Eng. Notes 28, 227–236 (2003)CrossRef
16.
Kalfoglou, Y., Schorlemmer, M.: Ontology mapping: the state of the art. In: Semantic Interoperability and Integration (2005)
17.
Bendaoud, R., Napoli, A., Toussaint, Y.: Formal Concept Analysis: A unified framework for building and refining ontologies. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 156–171. Springer, Heidelberg (2008)
18.
Stumme, G., Maedche, A.: Ontology merging for federated ontologies on the semantic web. In: International Workshop for Foundations of Models for Information, Integration (FMII-2001), pp. 413–418 (2001)
19.
Formica, A.: Ontology-based concept similarity in Formal Concept Analysis. Inf. Sci. 176, 2624–2641 (2006)CrossRef
20.
Tatsiopoulos, C., Boutsinas, B.: Ontology mapping based on association rule mining. In: International Conference on Enterprise Information Systems: Databases and Information Systems Integration (ICEIS 2009), pp. 33–40 (2009)
21.
Batini, C., Lenzerini, M., Navathe, S.B.: A comparative analysis of methodologies for database schema integration. ACM Comput. Surv. 18, 323–364 (1986)CrossRef
22.
Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB J 10, 334–350 (2001)CrossRef
23.
Shvaiko, P., Euzenat, J.: A Survey of Schema-Based Matching Approaches. In: Spaccapietra, S. (ed.) Journal on Data Semantics IV. LNCS, vol. 3730, pp. 146–171. Springer, Heidelberg (2005)
24.
Parent, C., Spaccapietra, S.: Issues and approaches of database integration. Commun. ACM 41, 166–178 (1998)CrossRef
25.
Doan, A., Halevy, A.Y.: Semantic integration research in the database community: A brief survey. AI Mag. 26, 83–94 (2005)
26.
Miralles, A., Gorretta, N., Miller, P.C., Walklate, P., Van Zuydam, R.P., Porskamp, H.A., Ganzelmeier, H., Rietz, S., Ade, G., Balsari, P., Vannucci, D., Planas, S.: Orchard sprayers:an european program to compare testing methods. In: International Symposium on Fruit Nut and Vegetable Production Production Engineering, Valencia Zaragoza, ESP, 22–26 mars 1993, pp. 117–122 (1994)
27.
Miralles, A., Polvêche, V.: Effects of the agrochemical products and adjuvants on spray quality and drift potential. In: 5th International Symposium on Adjuvants for Agrochemicals - ISAA ’98, Vol. 1, Memphis (USA), pp. 426–432 (1998)
Metadaten
Titel
Finding Semi-Automatically a Greatest Common Model Thanks to Formal Concept Analysis
verfasst von
Bastien Amar
Abdoulkader Osman Guédi
André Miralles
Marianne Huchard
Thérèse Libourel
Clémentine Nebut
Copyright-Jahr
2013
Verlag
Springer Berlin Heidelberg
Buch
Enterprise Information Systems

Print ISBN: 978-3-642-40653-9

Electronic ISBN: 978-3-642-40654-6

Copyright-Jahr: 2013

DOI
https://doi.org/10.1007/978-3-642-40654-6_5

Premium Partner

    Bildnachweise