Web usage mining for ontology management

Data Mining with Ontologies: Implementations, Findings, and Frameworks

Volumn , Issue , 2007, Pages 37-64

  Trousse, Brigitte ^a   Aufaure, Marie Aude ^a   Le Grand, Bénédicte ^b   Lechevallier, Yves ^c   Masseglia, Florent ^a  

^a INRIA   (France)

^b UNIVERSITÉ PIERRE ET MARIE CURIE   (France)

^c INRIA ROCQUENCOURT   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79851484765     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-59904-618-1.ch003     Document Type: Chapter

References (58)

1. Agirre, E., Ansa, O., Hovy, E., & Martinez, D. (2000). Enriching very large ontologies using the WWW. In Proceedings of ECAI Workshop on Ontology Learning.
2. Agrawal, R., & Srikant, R. (1995). Mining Sequential Patterns. In Proceedings of the 11th International Conference on Data Engineering (pp. 3-14).
3. ANSI/NISO. (1993). Guidelines for the construction, format, and management of monolingual thesauri. National Information Standards Organization.
4. Aussenac-Gilles, N., Biébow, B., & Szulman, S. (2002). Revisiting ontology design: A methodology based on corpus analysis. In Proceedings of the 12th International Conference in Knowledge Engineering and Knowledge Management (EKAW), Juan-Les-Pins, France.
5. AxIS. (2005). 2005 AxIS research project activity report. Section 'Overall Objectives.' http://www.inria.fr/rapportsactivite/RA2005/axis/axis_tf.html
6. Mustapha, N., Aufaure, M-A., & Baazhaoui-Zghal, H. (2006). Towards an architecture of ontological components for the semantic web. In Proceedings of Wism (Web Information Systems Modeling) Workshop, CAiSE 2006, Luxembourg (pp. 22-35).
7. Berendt, B., Hotho, A., & Stumme, G. (2002). Towards Semantic Web mining. In Proceedings of the First International Semantic Web Conference on the Semantic Web (pp. 264-278). Springer.
8. Berendt, B., Hotho, A., & Stumme, G. (2005, September 15-16). Semantic Web mining and the representation, analysis, and evolution of Web space. In Proceedings of RAWS'2005-Workshop on the Representation and Analysis of Web Space, Prague-Tocna.
9. Bock, H.H. (1993). Classification and clustering: Problems for the future. In E. Diday, Y. Lechevallier, M. Schader, P. Bertrand, & B. Burtschy, (Eds.), New approaches in classification and data analysis (pp. 3-24). Springer, Heidelberg.
10. Bonchi, F., Giannotti, F., Gozzi, C., Manco, G., Nanni, M., Pedreschi, D., et al. (2001). Web log data warehousing and mining for intelligent web caching. Data Knowledge Engineering, 39(2), 165-189.
11. Castano, S., Ferrara, A., & Montanelli, S. (2006). A matchmaking-based ontology evolution methodology. In Proceedings of the 3rd CAiSE IN-TEROP Workshop on Enterprise Modelling and Ontologies for Interoperability (EMOI - INTEROP 2006), Luxembourg.
12. Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., et al. (2000). Learning to construct knowledge bases from the World Wide Web. Artificial Intelligence, 118(1-2), 69-113.
13. Davulcu, H., Vadrevu, S., & Nagarajan, S. (2003). OntoMiner: Bootstrapping and populating ontologies from domain specific websites. In Proceedings of the First International Workshop on Semantic Web and Databases (SWDB 2003), Berlin.
14. Decker, S., Erdmann, M., Fensel, D., & Studer, R. (1999). Ontobroker: Ontology based access to distributed and semistructured information. In Semantic Issues in Multimedia Systems, Proceedings of DS-8 (pp. 351-369). Boston: Kluwer Academic Publisher.
15. Deitel, A.C., Faron, C. & Dieng, R. (2001). Learning ontologies from RDF annotations. In Proceedings of the IJCAI'01 Workshop on Ontology Learning, Seattle, WA.
16. Diday, E. (1975). La méthode des nuées dynamiques. Revue de Statistique Appliquée, 19(2), 19-34.
17. Euzenat, J. (1995). Building consensual knowledge bases: Context and architecture. In Proceedings of 2nd International Conference on Building and Sharing Very Large-Scale Knowledge Bases. Enschede, Amsterdam: IOS Press.
18. nd Workshop at ECML/PKDD-2002. Helsinki, Finland.
19. Flouris, G. (2006). On belief change and ontology evolution.Doctoral Dissertation, Department of Computer Science, University of Crete.
20. Flouris, G., & Plexousakis, D.G. (2006). Evolving ontology evolution, Invited Talk. In Proceedings of the 32nd International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM 06) (p. 7). Merin, Czech Republic.
21. Fu, Y., Sandhu, K., & Shih, M. (2000). A generalization-based approach to clustering of web usage sessions. In Proceedings of the 1999 KDD Workshop on Web Mining (Vol. 1836, pp. 21-38). San Diego, CA: Springer-Verlag.
22. Gerson, N., & Eick, S.G. (1995). Visualisation's new tack: Making sense of information. IEEE Spectrum, 38-56.
23. Gòmez-Pérez, A., & Rojas, M.D. (1999). Ontological reengineering and reuse. In D. Fensel & R. Studer (Ed.), European Workshop on Knowledge Acquisition, Modeling and Management (EKAW). Lecture Notes in Artificial Intelligence LNAI 1621 (pp. 139-156). Springer-Verlag.
24. Gordon, A.D. (1981). Classification: Methods for the exploratory analysis of multivariate data. London: Chapman & Hall.
25. Govaert, G. (1977). Algorithme de classification d'un tableau de contingence. In Proceedings of first international symposium on Data Analysis and Informatics (pp. 487-500). INRIA, Versailles.
26. Govaert, G., & Nadif, M. (2003). Clustering with block mixture models. Pattern recognition. Elservier Science Publishers, 36, 463-473.
27. Gruber, T. (1993). Toward principles for the design of ontologies used for knowledge sharing. In N. Guarino & R. Poli, (Eds.), International Journal of Human-Computer Studies, special issue on Formal Ontology in Conceptual Analysis and Knowledge Representation, LADSEB-CNR Int. Rep. ACM.
28. Grüninger, M., & Fox, M.S. (1995). Methodology for the design and evaluation of ontologies. IJCAI'95 Workshop on Basic Ontological Issues in Knowledge Sharing, Montreal, Canada.
29. Guarino, N. (1998). Formal Ontology in Information Systems. Guarino (Ed.), First International Conference on Formal Ontology in Information Systems (pp. 3-15). Italy.
30. Jannink, J. (1999). Thesaurus entry extraction from an on-line dictionary. In Proceedings of Fusion 99, Sunnyvale CA.
31. Junker, M., Sintek, M., & Rinck, M. (1999). Learning for Text Categorization and Information Extraction with ILP. In J. Cussens (Eds.), Proceedings of the 1st Workshop on Learning Language in Logic (pp. 84-93). Bled: Slovenia.
32. Karoui, L., Aufaure, M.-A., & Bennacer, N. (2004). Ontology discovery from web pages: Application to tourism. Workshop on Knowledge Discovery and Ontologies (KDO), co-located with ECML/PKDD, Pisa, Italy, pp. 115-120.
33. Kosala, R., & Blockeel, H. (2000). Web mining research: A survey. SIGKDD Explorations: Newsletter of the ACM Special Interest Group on Knowledge Discovery and Data Mining, 2(1), 1-5.
34. nd ed). Springer.
35. Masseglia, F., Poncelet, P., & Cicchetti, R. (1999). An efficient algorithm for web usage mining. Networking and Information Systems Journal (NIS), 2(5-6), 571-603.
36. Masseglia, F., Tanasa, D., & Trousse, B. (2004). Web usage mining: Sequential pattern extraction with a very low support. In Advanced Web Technologies and Applications: 6th Asia-Pacific Web Conference, APWeb 2004, vol. 3007 (pp. 513-522). Hangzhou, China: Springer-Verlag.
37. Nakagawa, M., & Mobasher, B. (2003). Impact of site characteristics on recommendation models based on association rules and sequential patterns. In Proceedings of the IJCAI'03 Workshop on Intelligent Techniques for Web Personalization, Acapulco, Mexico.
38. Navigli, R., & Velardi, P. (2004). Learning domain ontologies from document warehouses and dedicated web sites. Computational Linguistics, 30(2), 151-179.
39. Noy, N.F., & Klein, M. (2004). Ontology evolution: Not the same as schema evolution. Knowledge and Information Systems, 6(4), 428-440.
40. Papatheodrou, C., Vassiliou, A., & Simon, B. (2002). C. Papatheodrou, Discovery of ontologies for learning resources using word-based clustering. In Proceedings of ED MEDIA 2002, Denver.
41. Rahm, E., & Bernstein, P. (2001). A survey of approaches to automatic schema matching, The VLDB Journal, 334-350.
42. Rubin, D.L., Hewett, M., Oliver, D.E., Klein, T.E., & Altman, R.B. (2002). Automatic data acquisition into ontologies from pharmacogenetics relational data sources using declarative object definitions and XML. In Proceedings of the Pacific Symposium on Biology, Lihue, HI.
43. Sanchez, D., & Moreno, A. (2004). Automatic generation of taxonomies from the WWW. In Proceedings of the 5th International Conference on Practical Aspects of Knowledge Management (PAKM 2004). LNAI, Vol. 3336 (pp. 208-219). Vienna, Austria.
44. Sauberlich, F., & Huber, K.-P. (2001). A framework for web usage mining on anonymous logfile data. In Schwaiger M. & O. Opitz (Eds.), Exploratory data analysis in empirical research (pp. 309-318). Heidelberg: Springer-Verlag.
45. Spiliopoulou, M., Faulstich, L.C., & Winkler, K. (1999). A data miner analyzing the navigational behaviour of web users. In Proceedings of the Workshop on Machine Learning in User Modeling of the ACAI'99 Int. Conf., Creta, Greece.
46. nd European Workshop on the integration of knowledge, Semantic and Digital Media Technologies, London.
47. Staab, S., Schnurr, H.-P., Studer, R., & Sure, Y. (2001). Knowledge processes and ontologies. IEEE Intelligent Systems Special Issue on Knowledge Management, January/February, 16(1).
48. Stojanovic, L., Stojanovic, N., & Volz, R. (2002). Migrating data-intensive web sites into the semantic web. In Proceedings of the 17th ACM symposium on applied computing (SAC). ACM Press.
49. Stumme, G., Hotho, A., & Berendt, B. (2006). Semantic Web mining: State of the art and future directions. Journal of Web Semantics: Science, Services and Agents on the World Wide Web, 4(2), 124-143.
50. Suryanto, H., & Compton, P. (2001). Discovery of ontologies from knowledge bases. In Proceedings of the 1st International Conference on Knowledge Capture, the Association for Computing Machinery (pp. 171-178). New York.
51. Tanasa, D. (2005). Web usage mining: Contributions to intersites logs preprocessing and sequential pattern extraction with low support. PhD thesis, University of Nice Sophia Antipolis.
52. Tanasa, D., & Trousse, B. (2004). Advanced data preprocessing for intersites Web usage mining. IEEE Intelligent Systems, 19(2) 59-65.
53. Trousse, B., Jaczynski, M. & Kanawati, R. (1999). Using user behavior similarity for recommandation computation: The broadway approach. In Proceedings of 8th International Conference on Human Computer Interaction (HCI'99) (pp. 85-89). Munich:Lawrence Erlbaum.
54. Verde, R., & Lechevallier, Y. (2003). Crossed Clustering method on Symbolic Data tables. In M. Vichi, P. Monari, S. Migneni, & A. Montanari, (Eds.), New developments in classification, and data analysis (pp. 87-96). Heidelberg: Springer-Verlag.
55. Volz, R., Oberle, D., Staab, S., & Studer, R. (2003). OntoLiFT Prototype. IST Project 2001-33052 WonderWeb Deliverable.
56. Yuefeng, L., & Ning, Z. (2006). Mining ontology for automatically acquiring web user information needs. IEEE Trans. Knowl. Data Eng., 18(4), 554-568.
57. Zhang, T., Ramakrishnan, R., & Livny, M. (1996). Birch: An efficient data clustering method for very large databases. In H.V.Jagadish, & I.S. Mumick (Ed.), Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data (pp. 103-114). Montreal, Quebec, Canada: ACM Press.
58. Zhu, J., Hong, J., & Hughes, J.G. (2002). Using Markov Chains for link prediction in adaptive Web sites. In Proceedings of Soft-Ware 2002: First International Conferance on Computing in an Imperfect World (pp. 60-73). Belfast, UK.