Agents Based Ontological Mediation in IE Systems

  • Maria Teresa Pazienza
  • Michele Vindigni
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2700)


Building more adaptive SW applications is a crucial issue to scale up IE technology to the Web, where information is organized following different underlying knowledge and/or presentation models. Information agents are more and more being adopted to support extraction of relevant information from semi-structured web sources. To efficiently manage heterogeneous information sources they must be able to cooperate, to share their knowledge, and to agree upon appropriate terminology to be used during interaction. Being the internal knowledge representation possibly different for each participant, it reveals to be unfeasible to directly communicate concepts, while agents autonomy promotes abstraction from details about the internal structure of other agents. We will argue on main topics involved in adapting natural language to achieve semantic agreement in communication, and we will introduce a novel architecture based on a pool of intelligent agents. It will be done by defining a communication model that foresees a strong separation between terms and concepts, (being this difference often undervalued in the literature, where terms play the ambiguous roles of both concept labels and communication lexicon). For agents communicating through the language, lexical information embodies the possibility to “express” the underlying conceptualizations thus agreeing to a shared representation. To make the resulting architecture adaptive to the application domain three different agents typologies have been defined: resource agents, owning the target knowledge; service agents, providing basic skills to support complex activities and control agents, supplying the structural knowledge of the task, with coordination and control capabilities. We will focus on two dedicated service agents: a mediator, that will care about understanding the information an agent wants to express as well as the way to present it to others, and a translator, dealing with lexical misalignment due to different languages. The resulting agent community dynamically assumes the most appropriate configuration, in a transparent way with respect to the involved participants.


Knowledge Representation Service Agent Resource Agent Coordinator Agent Conceptual Plane 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Agirre e Rigau, 1996]
    Agirre, E., Rigau, G.: Word sense disambiguation using conceptual density. In: Proceedings of COLING 1996, Copenhagen, Danmark (1996)Google Scholar
  2. [Babylon, 1999]
    Babylon Translator, avilable at
  3. [Baldonado et al., 1997]
    Baldonado, M., Chang, C.-C.K., Gravano, L., Paepcke, A.: Metadata for digital libraries: Architecture and design rationale. Technical Report SIDL-WP- 1997-0055, Stanford University (1997)Google Scholar
  4. [Bateman et al., 1990]
    Bateman, J.A., Kasper, R.T., Moor, J.D., Whitney, R.A.: A general organization of knowledge for natural language processing: The penman upper model. Technical report, USC/Information Sciences Institute (1990)Google Scholar
  5. [Batini et al. 1986]
    Batini, C., Lenzerini, M., Navathe, S.B.: A comparative analysis of methodologies for database schema integration. ACM Computing Survey 18 (1986)CrossRefGoogle Scholar
  6. [Bayardo et al., 1997]
    Bayardo, R., Bohrer, W., Brice, R., Cichocki, A., Fowler, G., Helal, A., Kashyap, V., Ksiezyk, T., Martin, G., Nodine, M., Rashid, M., Rusinkiewicz, M., Shea, R., Unnikrishnan, C., Unruh, A., Woelk, D.: Infosleuth: Semantic Integration of Information in Open and Dynamic Environments. In: Proceedings ACM SIGMOD 1997 Conference (1997)Google Scholar
  7. [Benjamins e Fensel, 1998]
    Benjamins, R., Fensel, D.: Community is Knowledge! in (KA) 2. In: Proceedings of the 11th Banff Knowledge Acquisition for Knowledge-Based System Workshop (KAW 1998), Banff, Canada (1998)Google Scholar
  8. [Bobrow e Winograd, 1985]
    Bobrow, D., Winograd, T.: An overview of KRL, a Knowledge Representation Language. In: Readings in Knowledge Representation. Morgan Kaufmann, San Francisco (1985)Google Scholar
  9. [Bray et al., 1998]
    Bray, T., Paoli, J., Sperberg-McQueen, C.M. (eds.): XML Extensible Markup Language (XML) 1.0, February 10 (1998), Available at
  10. [Bright et al., 1994]
    Bright, M.W., Hurson, A.R., Pakzad, S.: Automated Resolution of Semantic Heterogeneity in Multidatabases. ACM Transactions on Database Systems 19(2) (1994)CrossRefGoogle Scholar
  11. [Campbell e Shapiro, 1995]
    Campbell, A.E., Shapiro, S.C.: Ontologic Mediation: An Overview. In: IJCAI 1995 Workshop on Basic Ontological Issues in Knowledge Sharing, Montreal (1995)Google Scholar
  12. [Campbell, 1999]
    Campbell, A.E.: Ontological Mediation: Finding Translations Across Dialects by Asking questions, Phd. Dissertation submitted to the University of New York, Buffalo (1999)Google Scholar
  13. [Campbell, 1996]
    Campbell, A.E.: Resolution of the Dialect Problem in Communication through Ontological Mediation. In: Proceedings of the AAAI 1996 Workshop on Detecting, Preventing, and Repairing Human-Machine Miscommunication, Portland, OR (1996)Google Scholar
  14. [Catarci e Lenzerini, 1993]
    Catarci, T., Lenzerini, M.: Representing and using interschema knowledge in cooperative information systems. Journal of Intelligent and Cooperative Information Systems 2(4) (1993)Google Scholar
  15. [Chang e Garcia-Molina, 1998]
    Chang, C.-C.K., Garcia-Molina, H.: Conjunctive constraint mapping for data translation. In: Proc. of the Third ACM Intl. Conf. on Digital Libraries, Pittsburgh, PA (1998)Google Scholar
  16. [Chawathe et al., 1994]
    Chawathe, S., Garcia-Molina, H., Hammer, J., Ireland, K., Papakonstantinou, Y., Ullman, J., Widom, J.: The TSIMMIS Project: Integration of Heterogeneous Information Sources. In: Proc. of IPSJ Conference (1994)Google Scholar
  17. [Clark, 1983]
    Clark, E.V.: Meanings and concepts. In: Mussen, P. (ed.) Manual of child psychology, vol. 3, pp. 787–840. Wiley, New York (1983)Google Scholar
  18. [Cohen e Hirsh, 1994]
    Cohen, W.W., Hirsh, H.: The learnability of description logics with equality constraints. Machine Learning 17 (1994)CrossRefGoogle Scholar
  19. [Cohen e Levesque, 1995]
    Cohen, P.R., Levesque, H.J.: Communicative actions for artificial agents. In: Proceedings of the First International Conference on Multi-Agent Systems (ICMAS 1995), Menlo Park, California (1995)Google Scholar
  20. [Cohen e Levesque, 1990]
    Cohen, P.R., Levesque, H.J.: Rational interaction as the basis for communication. In: Cohen, P.R., Morgan, J., Pollack, M.E. (eds.) Intentions in Communication. The MIT Press, Cambridge (1990)Google Scholar
  21. [Collins e Quillian, 1969]
    Collins, A.M., Quillian, M.R.: Retrieval time for semantic memory. Journal of Verbal Learning and Verbal Behaviour 8 (1969)CrossRefGoogle Scholar
  22. [Dale et al., 2001]
    Dale, J., Mamdani, E.: Open Standards for Interoperating Agent-Based Systems. Software Focus 1(2) (2001)Google Scholar
  23. [Decker et al., 1996]
    Decker, K., Williamson, M., Sycara, K.: Modeling information agents: Advertisements, organizational roles, and dynamic behavior. In: Proceedings of the AAAI 1996 Workshop on Agent Modeling (1996)Google Scholar
  24. [Drogoul e Ferber, 1994]
    Drogoul, A., Ferber, J.: Multi-agent simulation as a tool for studying emergent processes in societies. In: Doran, J., Gilbert, G.N. (eds.) Simulating Societies: the Computer Simulation of Social Phenomena, ULCP, London (1994)Google Scholar
  25. [Ferber, 1999]
    Ferber, J.: Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Reading (1999)Google Scholar
  26. [Fikes et al., 1991]
    Fikes, R., Cutkosky, M., Gruber, T., Baalen, J.V.: Knowledge Sharing Technology Project Overview. Technical Report KSL-91-71, Knowledge Systems Laboratory, Stanford University (1991)Google Scholar
  27. [Finin e Weiderhold, 1991]
    Finin, T., Weiderhold, G.: An Overview of KQML: A Knowledge Query and Manipulation Language. Available through the Stanford University Computer Science Department (1991)Google Scholar
  28. [Franklin e Graesser, 1996]
    Franklin, S., Graesser, A.: Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents. In: Proc. of the Third International Workshop on Agent Theories, Architectures and Languages (1996)Google Scholar
  29. [Gruber, 1992]
    Gruber, T.R.: ONTOLINGUA: A Mechanism to Support Portable Ontologies, technical report, Knowledge Systems Laboratory, Stanford University, Stanford, United States (1992)Google Scholar
  30. [Guarino, 1998]
    Guarino, N.: Formal Ontology and Information Systems. In: Guarino, N. (ed.) Proceedings of the 1st International Conference on Formal Ontologies in Information Systems, FOIS 1998, Trento, Italy. IOS Press, Amsterdam (1998)Google Scholar
  31. [Guha e Lenat, 1990]
    Guha, R.V., Lenat, D.B.: Building Large Knowledge-Based Systems: Representation and Inference in the CYC Project. Addison-Wesley, Reading (1990)Google Scholar
  32. [Guha e Lenat, 1994]
    Guha, R.V., Lenat, D.B.: Enabling agents to work together. Communications of the ACM 37(7) (1994)CrossRefGoogle Scholar
  33. [Gustavsson, 1997]
    Gustavsson, R.: Multi Agent Systems as Open Societies. In: Rao, A., Singh, M.P., Wooldridge, M.J. (eds.) ATAL 1997. LNCS, vol. 1365. Springer, Heidelberg (1998)Google Scholar
  34. [Haas e Hendrix, 1983]
    Haas, N., Hendrix, G.: Learning by being told: Acquiring knowledge for information management. In: Michalski, R., Carbonell, J., Mitchell, T. (eds.) Machine Learning: An Artificial Intelligence Approach, vol. 1 ch. 13. Morgan Kaufmann Publishers, Inc., San Francisco (1983)Google Scholar
  35. [Heflin et al. 1999]
    Heflin, J., Hendler, J., Luke, S.: SHOE: A Knowledge Representation Language for Internet Applications. Technical Report CS-TR-4078 (UMIACS TR-99-71), Dept. of Computer Science, University of Maryland at College Park (1999)Google Scholar
  36. [Hull, 1997]
    Hull, R.: Managing semantic heterogeneity in databases: A theoretical perspective. In: Proc. ACM Symposium on Principles of Databases (1997)Google Scholar
  37. [Jones e Paton, 1998]
    Jones, D.M., Paton, R.C.: Some Problems in the Formal Representation of Hierarchical Relationships. In: Proc. Conference on Formal Ontology in Information Systems – FOIS 1998, Trento, Italy. IOS Press, Amsterdam (1998)Google Scholar
  38. [Kashyap e Sheth, 1996]
    Kashyap, V., Sheth, A.: Semantic and Schematic Similarities between Database Objects: A Context-based Approach. VLDB Journal 5(4) (1996)CrossRefGoogle Scholar
  39. [Khedro e Genesereth, 1994]
    Khedro, T., Genesereth, M.: The federation architecture for interoperable agent-based concurrent engineering systems. International Journal on Concurrent Engineering, Research and Applications 2 (1994)CrossRefGoogle Scholar
  40. [Khedro e Genesereth, 1995]
    Khedro, T., Genesereth, M.: Facilitators: A networked computing infrastructure for distributed software interoperation. In: Working Notes of the IJCAI 1995 Workshop on Artificial Intelligence in Distributed Information Networks (1995)Google Scholar
  41. [Kim e Seo, 1991]
    Kim, W., Seo, J.: Classifying schematic and data heterogeneity in multidatabase systems. IEEE Computer 24(12) (1991)CrossRefGoogle Scholar
  42. [Knight e Luk, 1994]
    Knight, K., Luk, S.K.: Building a Large-Scale Knowledge Base for Machine Translation. In: Proceedings of the AAAI 1994 (1994)Google Scholar
  43. [Knoblock e Ambite, 1997]
    Knoblock, C.A., Ambite, J.-L.: Agents for information gathering. In: Bradshaw, J. (ed.) Software Agents, AAAI/MIT Press, Menlo Park/CA (1997)Google Scholar
  44. [Kuhn, 1993]
    Kuhn, N., Müller, H.J., Müller, J.P.: Task Decomposition in Dynamic Agent Societies. In: Müller, J.P., Castelfranchi, C. (eds.) MAAMAW 1993. LNCS, vol. 957. Springer, Heidelberg (1995)Google Scholar
  45. [Lehmann e Cohn, 1994]
    Lehmann, F., Cohn, A.G.: The EGG/YOLK reliability hierarchy: Semantic data integrationusing sorts with prototypes. In: Proc. Conf. on Information Knowledge Management. ACM Press, New York (1994)Google Scholar
  46. [Levy et al., 1996]
    Levy, A., Rajaraman, A., Ordille, J.: Query answering algorithms for information agents. In: Proceedings of the 13th National Conference on Artificial Intelligence (1996)Google Scholar
  47. [Li, 1995]
    Li, W.-S.: Knowledge gathering and matching in heterogeneous databases. In: Working Notes of the AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments (1995)Google Scholar
  48. [Martin et al., 1999]
    Martin, G.L., Unruh, A., Urban, S.D.: An Agent Infrastructure for Knowledge Discovery and Event Detection (1999), Available at
  49. [Miller et al., 1993]
    Miller, G., Beckwith, R., Fellbaum, C., Gross, D.,, D., Miller, K.: Introduction to WordNet: An on-line lexical database. In: Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (1993)Google Scholar
  50. [Miller, 1985]
    Miller, G.: WORDNET: A Dictionary Browser. In: Proceedings of the First International Conference on Information in Data, University of Waterloo Centre for the New OED, Waterloo, Ontario (1985)Google Scholar
  51. [Moore, 1990]
    Moore, R.C.: A formal theory of knowledge and action. In: Allen, J.F., Hendler, J., Tate, A. (eds.) Readings in Planning. Morgan Kaufmann Publishers, San Mateo (1990)Google Scholar
  52. [Park et al., 1998]
    Park, J.Y., Gennari, J.H., Musen, M.A.: Mappings for Reuse in Knowledge-based Systems. In: 11th Workshop on Knowledge Acquisition, Modelling and Management KAW 1998, Banff, Canada (1998)Google Scholar
  53. [Pazienza, 2002]
    Pazienza, M.T.: Intelligent-Agents need ontologies: Why, What, Where, When, Who. In: Proceedings of the workshop OMAS Ontologies for Multi-Agent Systems, Siguenza, Spain, September 30 (2002)Google Scholar
  54. [Pazienza and Vindigni, 2002a]
    Pazienza, M.T., Vindigni, M.: Mining linguistic information into an e-retail system. In: Proceedings of the DATA MINING 2002 Conference, Bologna, September 23–25 (2002)Google Scholar
  55. [Pazienza and Vindigni, 2002b]
    Pazienza, M.T., Vindigni, M.: Language-based agent communication. In: Proceedings of the EKAW 2002 Conference, workshop OMAS Ontologies for Multi-Agent Systems, Siguenza, Spain, September 30 (2002)Google Scholar
  56. [Peirce, 1932]
    Peirce, C.S.: Elements of logic. In: Hartshorne, C., Weiss, P. (eds.) Collected Papers of Charles Sanders Peirce, vol. 2. Harvard University Press, Cambridge (1932)Google Scholar
  57. [Ramesh e Ram, 1997]
    Ramesh, V., Ram, S.: Integrity Constraint Integration in Heterogeneous Databases: An Enhanced Methodology for Schema Integration. Information Systems 22, 8 (1997)CrossRefGoogle Scholar
  58. [Sheth et al., 1993]
    Sheth, A.P., Gala, S.K., Navathe, S.B.: On automatic reasoning for schema integration. International Journal of Intelligent and Cooperative Information Systems 2(1) (1993)Google Scholar
  59. [Sowa, 2000]
    Sowa, J.F.: Knowledge Representation: Logical, Philosophical, and Computational Foundations. Brooks Cole Publishing Co., Pacific Grove (2000)Google Scholar
  60. [Sowa,2000bis]
    Sowa, J.F.: Ontology, Metadata, and Semiotics. In: Ganter, B., Mineau, G.W. (eds.) ICCS 2000. LNCS (LNAI), vol. 1867, pp. 55–81. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  61. [Sycara et al., 1998]
    Sycara, K., Lu, J., Klusch, M.: Interoperability among Heterogeneous Software Agents on the Internet. Carnegie Mellon University, PA (USA), Technical Report CMU-RI-TR-98-22 (1998)Google Scholar
  62. [Takeda et al., 1995]
    Takeda, H., Iino, K., Nishida, T.: Agent organisation with multiple ontologies. International Journal of Cooperative Information Systems 4(4) (1995)Google Scholar
  63. [Visser et al., 1997]
    Visser, P.R.S., Jones, D.M., Bench-Capon, T.J.M., Shave, M.J.R.: An Analysis of Ontology Mismatches: Heterogeneity versus Interoperability. In: Presented at AAAI 1997 Spring Symposium on Ontological Engineering, Stanford University, CA (1997)Google Scholar
  64. [Widerhold and Genesereth, 1997]
    Wiederhold, G., Genesereth, M.: The conceptual basis for mediation services. IEEE Intelligent Systems, 38–47 (September/October 1997)Google Scholar
  65. [Weinstein e Birmingham, 1998]
    Weinstein, P.C., Birmingham, W.P.: Creating Ontological Metadata for Digital Library Content and Services. International Journal on Digital Libraries 2(1) (1998)CrossRefGoogle Scholar
  66. [Woolridge e Jennings, 1995]
    Woolridge, M., Jennings, N.R.: Agent Theories, Architectures and Languages: A Survey. In: Woolridge, M.J., Jennings, N.R. (eds.) Proc. of the ECAI 1994 Workshop on Agent Theories, Architectures and Languages. Springer, Berlin (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Maria Teresa Pazienza
    • 1
  • Michele Vindigni
    • 1
  1. 1.Department of Computer Science, systems and ProductionUniversity of Roma “Tor Vergata”Italy

Personalised recommendations