Linkage of Heterogeneous Knowledge Resources within In-Store Dialogue Interaction

  • Sabine Janzen
  • Tobias Kowatsch
  • Wolfgang Maass
  • Andreas Filler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6497)


Dialogue interaction between customers and products improves presentation of relevant product information in in-store shopping situations. Thus, information needs of customers can be addressed more intuitive. In this article, we describe how access to product information can be improved based on dynamic linkage of heterogeneous knowledge representations. We therefore introduce a conceptual model of dialogue interaction based on multiple knowledge resources for in-store shopping situations and empirically test its utility with end-users.


heterogeneous knowledge resources dynamic linkage dialogue interaction ontology empirical study 


  1. 1.
    Gurevych, I., Mühlhäuser, M.: Natural language processing for ambient intelligence. Künstliche Intelligenz/Special Issue: Ambient Intelligence und Künstliche Intelligenz (2), 10–16 (2007)Google Scholar
  2. 2.
    Sabou, M., Kantorovitch, J., Nikolov, A., Tokmakoff, A., Zhou, X., Motta, E.: Position paper on realizing smart products: Challenges for semantic web technologies. In: The 2nd International Workshop on Semantic Sensor Networks, collocated with ISWC 2009 (2009)Google Scholar
  3. 3.
    Bel-Enguix, G., Dediu, A.-H., Jimenez-Lopez, M.: A dialogue-based system for man-machine interaction. In: Conf. on Human System Interactions, pp. 141–146 (25-27, 2008)Google Scholar
  4. 4.
    Catizone, R., Wilks, Y., Worgan, S., Turunen, M.: Some background on dialogue management and conversational speech for dialogue systems. In: Wilks, Y., Catizone, R. (eds.) Computer, Speech and Language (2010) (special issue on dialogue)Google Scholar
  5. 5.
    Warren, H.D.D., Pereira, C.N.F.: An efficient easily adaptable system for interpreting natural language queries. Computational Linguistics (8), 110–122 (1982)Google Scholar
  6. 6.
    Clark, P., Chaw, S.Y., Barker, K., Chaudhri, V., Harrison, P., Fan, J., John, B., Porter, B., Spaulding, A., Thompson, J., Yeh, P.: Capturing and answering questions posed to a knowledge-based system. In: K-CAP 2007: Proc. of the 4th International Conf. on Knowledge Capture, pp. 63–70. ACM, New York (2007)Google Scholar
  7. 7.
    Alexandersson, J., Becker, T., Pfleger, N.: Overlay: The basic operation for discourse processing. In: Wahlster, W. (ed.) SmartKom: Foundations of Multimodal Dialogue Systems, pp. 255–267 (2006)Google Scholar
  8. 8.
    Perez, G., Amores, G., Manchon, P., Gonzalez, O.G.Y.J., Julietta, G.I.: Integrating owl ontologies with a dialogue manager. Technical report, CiteSeerX - Scientific Literature Digital Library and Search Engine (2006)Google Scholar
  9. 9.
    Chen, Y.J., Chen, Y.M., Chu, H.C.: Development of a mechanism for ontology-based product lifecycle knowledge integration. Expert Syst. Appl. 36(2), 2759–2779 (2009)CrossRefGoogle Scholar
  10. 10.
    Hepp, M.: Goodrelations: An ontology for describing products and services offers on the web. In: Gangemi, A., Euzenat, J. (eds.) EKAW 2008. LNCS (LNAI), vol. 5268, pp. 329–346. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  11. 11.
    Ou, S., Pekar, V., Orasan, C., Spurk, C., Matteo, N.: Development and alignment of a domain-specific ontology for question answering. In: European Language Resources Association (ed.) Proc. of the Sixth International Language Resources and Evaluation (LREC 2008), Marrakech, Morocco (2008)Google Scholar
  12. 12.
    Clark, P., Thompson, J., Porter, B.: A knowledge-based approach to question-answering. In: Proc. AAAI 1999 Fall Symposium on Question-Answering Systems, pp. 43–51 (1999)Google Scholar
  13. 13.
    Buitelaar, P., Declerck, T., Calzolari, N., Lenci, A.: Language resources and the semantic web. In: Proc. of the ELSNET/ENABLER Workshop (2003)Google Scholar
  14. 14.
    Lopez, V., Uren, V., Motta, E., Pasin, M.: AquaLog: an ontology-driven question answering system for organizational semantic intranets. Web Semantics 5(2), 72–105 (2008)CrossRefGoogle Scholar
  15. 15.
    Hayashi, Y., Declerck, T., Buitelaar, P., Monachini, M.: Ontologies for a global language infrastructure. In: Webster, J., Ide, N., Fang, A.C. (eds.) Proc. of the 1st International Conf. on Global Interoperability for Language Resources (ICGL 2008), Hong Kong, China, pp. 105–112 (2008)Google Scholar
  16. 16.
    Anderl, R., Trippner, D.: Step standard for the exchange of product model data. Technical report, STEP (2000)Google Scholar
  17. 17.
    Kowatsch, T., Maass, W.: Towards a framework for knowledge-based pricing services improving operational agility in the retail industry. In: D’Andrea, V., Gangadharan, G.R., Iannella, R., Weiss, M. (eds.) CEUR Workshop Proc., vol. 530 (2009)Google Scholar
  18. 18.
    Kowatsch, T., Maass, W., Filler, A., Janzen, S.: Knowledge-based bundling of smart products on a mobile recomendation agent. In: ICMB 2008: Proc. of the 7th International Conf. on Mobile Business, Washington, DC, USA, pp. 181–190. IEEE Computer Society, Los Alamitos (2008)Google Scholar
  19. 19.
    Maass, W., Janzen, S.: A pattern-based ontology building method for ambient environments. In: Blomqvist, E., Sandkuhl, K., Scharffe, F., Svatek, V. (eds.) Proc. of the Workshop on Ontology Patterns (WOP 2009), collocated with ISWC 2009, Washington D.C., vol. 516, CEUR Workshop Proc. (2009)Google Scholar
  20. 20.
    Maass, W., Filler, A.: Towards an infrastructure for semantically annotated physical products. In: Gesellschaft für Informatik e. V (ed.) Conf. Proc. Informatik 2006 (2006)Google Scholar
  21. 21.
    Janzen, S., Maass, W.: Ontology-based natural language processing for in-store shopping situations. In: Proc. of Third IEEE International Conf. on Semantic Computing (ICSC 2009), pp. 361–366. IEEE Computer Society, Los Alamitos (2009)CrossRefGoogle Scholar
  22. 22.
    Marcus, M.P., Marcinkiewicz, M.A., Santorini, B.: Building a large annotated corpus of english: the penn treebank. Comput. Linguist. 19(2), 313–330 (1993)Google Scholar
  23. 23.
    Kamis, A., Koufaris, M., Stern, T.: Using an attribute-based decision support system for user-customized products online: An experimental investigation. MIS Quarterly 32(1), 159–177 (2008)Google Scholar
  24. 24.
    Moore, G., Benbasat, I.: Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research 2, 173–191 (1991)CrossRefGoogle Scholar
  25. 25.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3), 319–339 (1989)CrossRefGoogle Scholar
  26. 26.
    Nunnally, J.C.: Psychometric Theory. McGraw-Hill, New York (1967)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Sabine Janzen
    • 1
  • Tobias Kowatsch
    • 2
  • Wolfgang Maass
    • 1
    • 2
  • Andreas Filler
    • 1
  1. 1.Furtwangen UniversityFurtwangenGermany
  2. 2.University of St. GallenSt. GallenSwitzerland

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