Abstract
Knowledge Engineering is a costly, tedious and often time-consuming task, for which light-weight processes are desperately needed. In this paper, we present a new paradigm - Navigation-induced Knowledge Engineering by Example (NKE) - to address this problem by producing structured knowledge as a result of users navigating through an information system. Thereby, NKE aims to reduce the costs associated with knowledge engineering by framing it as navigation. We introduce and define the NKE paradigm and demonstrate it with a proof-of-concept prototype which creates OWL class expressions based on users navigating in a collection of resources. The overall contribution of this paper is twofold: (i) it introduces a novel paradigm for knowledge engineering and (ii) it provides evidence for its technical feasibility.
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References
Baader, F., Ganter, B., Sattler, U., Sertkaya, B.: Completing description logic knowledge bases using formal concept analysis. In: IJCAI 2007. AAAI Press (2007)
Baader, F., Sertkaya, B., Turhan, A.-Y.: Computing the least common subsumer w.r.t. a background terminology. J. Applied Logic 5(3), 392–420 (2007)
Cimiano, P., Rudolph, S., Hartfiel, H.: Computing intensional answers to questions - an inductive logic programming approach. Journal of Data and Knowledge Engineering, DKE (2009)
Cohen, W.W., Hirsh, H.: Learning the CLASSIC description logic: Theoretical and experimental results. In: Doyle, J., Sandewall, E., Torasso, P. (eds.) Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning, pp. 121–133. Morgan Kaufmann (May 1994)
Esposito, F., Fanizzi, N., Iannone, L., Palmisano, I., Semeraro, G.: Knowledge-intensive induction of terminologies from metadata. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 441–455. Springer, Heidelberg (2004)
Heim, P., Hellmann, S., Lehmann, J., Lohmann, S., Stegemann, T.: RelFinder: Revealing relationships in RDF knowledge bases. In: Chua, T.-S., Kompatsiaris, Y., Mérialdo, B., Haas, W., Thallinger, G., Bailer, W. (eds.) SAMT 2009. LNCS, vol. 5887, pp. 182–187. Springer, Heidelberg (2009)
Helic, D., Strohmaier, M., Trattner, C., Muhr, M., Lerman, K.: Pragmatic evaluation of folksonomies. In: 20th International World Wide Web Conference (WWW 2011), Hyderabad, India, March 28-April 1, pp. 417–426. ACM (2011)
Helic, D., Trattner, C., Strohmaier, M., Andrews, K.: On the navigability of social tagging systems. In: The 2nd IEEE International Conference on Social Computing (SocialCom 2010), Minneapolis, Minnesota, USA, pp. 161–168 (2010)
Hellmann, S., Lehmann, J., Auer, S.: Learning of OWL class descriptions on very large knowledge bases. Int. J. Semantic Web Inf. Syst. 5(2), 25–48 (2009)
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)
Iannone, L., Palmisano, I., Fanizzi, N.: An algorithm based on counterfactuals for concept learning in the semantic web. Applied Intelligence 26(2), 139–159 (2007)
Jarrar, M., Meersman, R.: Formal ontology engineering in the DOGMA approach. In: Meersman, R., Tari, Z. (eds.) CoopIS/DOA/ODBASE 2002. LNCS, vol. 2519, pp. 1238–1254. Springer, Heidelberg (2002)
Kim, H.L., Scerri, S., Breslin, J.G., Decker, S., Kim, H.G.: The State of the Art in Tag Ontologies: A Semantic Model for Tagging and Folksonomies. In: Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications, Berlin, Deutschland, pp. 128–137. Dublin Core Metadata Initiative (2008)
Koerner, C., Benz, D., Strohmaier, M., Hotho, A., Stumme, G.: Stop thinking, start tagging - tag semantics emerge from collaborative verbosity. In: Proc. of the 19th International World Wide Web Conference (WWW 2010), Raleigh, NC, USA. ACM (April 2010)
Lehmann, J.: DL-Learner: learning concepts in description logics. JMLR 2009 (2009)
Lehmann, J., Bizer, C., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: DBpedia - a crystallization point for the web of data. Journal of Web Semantics 7(3), 154–165 (2009)
Lehmann, J., Haase, C.: Ideal downward refinement in the \(\mathcal{EL}\) description logic. In: De Raedt, L. (ed.) ILP 2009. LNCS, vol. 5989, pp. 73–87. Springer, Heidelberg (2010)
Lehmann, J., Hitzler, P.: A refinement operator based learning algorithm for the \(\mathcal{ALC}\) description logic. In: Blockeel, H., Ramon, J., Shavlik, J., Tadepalli, P. (eds.) ILP 2007. LNCS (LNAI), vol. 4894, pp. 147–160. Springer, Heidelberg (2008)
Lehmann, J., Hitzler, P.: Concept learning in description logics using refinement operators. Machine Learning Journal 78(1-2), 203–250 (2010)
Lehmann, J., Knappe, S.: DBpedia navigator. In: Semantic Web Challenge, International Semantic Web Conference 2008 (2008)
López, M.M.F.: Overview of Methodologies for Building Ontologies. In: Proceedings of the IJCAI 1999 Workshop on Ontologies and Problem Solving Methods (KRR5), Stockholm, Sweden, August 2 (1999)
Pinto, H.S., Martins, J.P.: Ontologies: How can they be built? Knowledge and Information Systems 6(4), 441–464 (2004)
Rudolph, S.: Exploring relational structures via \({\mathcal{F\!LE}}\). In: Wolff, K.E., Pfeiffer, H.D., Delugach, H.S. (eds.) ICCS 2004. LNCS (LNAI), vol. 3127, pp. 196–212. Springer, Heidelberg (2004)
Siorpaes, K., Hepp, M.: OntoGame: Weaving the semantic web by online games. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 751–766. Springer, Heidelberg (2008)
Strohmaier, M., Koerner, C., Kern, R.: Why do users tag? Detecting users’ motivation for tagging in social tagging systems. In: International AAAI Conference on Weblogs and Social Media (ICWSM 2010), Menlo Park, CA, USA. AAAI (2010)
Studer, R., Benjamins, R., Fensel, D.: Knowledge engineering: Principles and methods. Data & Knowledge Engineering 25(1-2), 161–198 (1998)
Völker, J., Rudolph, S.: Fostering web intelligence by semi-automatic OWL ontology refinement. In: Web Intelligence, pp. 454–460. IEEE (2008)
Ziegler, C.-N., Lausen, G., Konstan, J.A.: On exploiting classification taxonomies in recommender systems. AI Commun. 21(2-3), 97–125 (2008)
Zubiaga, A., Koerner, C., Strohmaier, M.: Tags vs shelves: from social tagging to social classification. In: Proceedings of the 22nd ACM Conference on Hypertext and Hypermedia, pp. 93–102. ACM (2011)
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Hellmann, S., Lehmann, J., Unbehauen, J., Stadler, C., Lam, T.N., Strohmaier, M. (2013). Navigation-Induced Knowledge Engineering by Example. In: Takeda, H., Qu, Y., Mizoguchi, R., Kitamura, Y. (eds) Semantic Technology. JIST 2012. Lecture Notes in Computer Science, vol 7774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37996-3_14
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DOI: https://doi.org/10.1007/978-3-642-37996-3_14
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