A. Table, 1: List of Semantic Topics for www.inria.fr and www-sop.inria.fr

. Abcinteactive and . Com, Spiders and Robots

A. [. Azcarraza and . Giacometti, A Prototype-Based Incremental Network Model for Classification Task, Proceedings of the Forth International Conference on Neural Networks and Their Applications, pp.121-134, 1991.

T. [. Agrawal, A. Imielinski, and . Swami, Mining Association Rules between Sets of Items in Large Databases, Proc. of the 1993 ACM SIGMOD Conference, pp.207-216, 1993.

]. J. Alt72 and . Altman, Postnatal Development of the Cerebellar Cortex in the Rat, Journal of Comparative Neurology, vol.145, issue.3-4, pp.353-513, 1972.

M. Arnoux, Y. Lechevallier, D. Tanasa, B. Trousse, and R. Verde, Automatic Clustering for the Web Usage Mining, Proceedings of the Fifth International Workshop on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC03), pp.54-66

D. Lechevallier, B. Tanasa, R. Trousse, and . Verde, Classification automatiquè a partir de logs web et de connaissances sur le site, Atelier " Fouille de Données Complexes, pp.59-72, 2004.

R. [. Agrawal and . Srikant, Fast Algorithms for Mining Association Rules, Proceedings of the Twentieth International Conference on Very Large Data Bases, VLDB, pp.487-499, 1994.

R. [. Agrawal and . Srikant, Mining sequential patterns, Proceedings of the Eleventh International Conference on Data Engineering, pp.3-14, 1995.
DOI : 10.1109/ICDE.1995.380415

L. [. De-bra, V. Aroyo, and . Chepegin, The Next Big Thing: Adaptive Web-Based Systems, Journal of Digital Information, vol.5, issue.247, 2004.

. Bgg-+-01-]-f, F. Bonchi, C. Giannotti, G. Gozzi, M. Manco et al., Web Log Data Warehousing and Mining for Intelligent Web Caching, Data Knowledge Engineering, vol.39, issue.2, pp.165-189, 2001.

A. [. Berendt, G. Hotho, and . Stumme, Towards Semantic Web Mining, Proceedings of the First International Semantic Web Conference on The Semantic Web (ISWC'02), pp.264-278, 2002.
DOI : 10.1007/3-540-48005-6_21

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.2066

R. [. Berners-lee, L. Fielding, and . Masinter, Uniform Resource Identifiers (URI): Generic Syntax, Network Working Group RFC, vol.2396, 1998.
DOI : 10.17487/rfc2396

B. [. Berendt, M. Mobasher, M. Nakagawa, and . Spiliopoulou, The Impact of Site Structure and User Environment on Session Reconstruction in Web Usage Analysis, Proceedings of the Forth WebKDD, 2002.
DOI : 10.1007/978-3-540-39663-5_10

B. [. Berendt, M. Mobasher, J. Spiliopoulou, and . Wiltshire, Measuring the Accuracy of Sessionizers for Web Usage Analysis, Proceedings of the Workshop on Web Mining at the First SIAM International Conference on Data Mining, 2001.

M. [. Berendt and . Spiliopoulou, Analysis of navigation behaviour in web sites integrating multiple information systems, The VLDB Journal, vol.9, issue.1, pp.56-75, 2000.
DOI : 10.1007/s007780050083

B. [. Benedek and . Trousse, Adaptation of Self-Organizing Maps for CBR Case Indexing, Proceedings of the Forth International Workshop on Symbolic and Numeric Algorithms for Scientific Computing 27th Annual Conference of the Gesellschaft fur Klassifikation, pp.31-45, 2002.

. V. Chm-+-00-]-i, D. Cadez, C. Heckerman, P. Meek, S. Smyth et al., Visualization of Navigation Patterns on a Web Site Using Model-Based Clustering, Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.280-284, 2000.

A. [. Cimiano, S. Hotho, and . Staab, Comparing Conceptual, Divise and Agglomerative Clustering for Learning Taxonomies from Text, Proceedings of the Sixteenth Eureopean Conference on Artificial Intelligence, ECAI'2004, including Prestigious Applicants of Intelligent Systems, pp.435-439, 2004.

B. [. Cooley, J. Mobasher, and . Srivastava, Data Preparation for Mining World Wide Web Browsing Patterns, Knowledge and Information Systems, vol.27, issue.6, pp.5-32, 1999.
DOI : 10.1007/BF03325089

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.3835

]. R. Coo00 and . Cooley, Web Usage Mining: Discovery and Application of Interesting Patterns from Web Data, 2000.

]. R. Coo03 and . Cooley, The Use of Web Structure and Content to Identify Subjectively Interesting Web Usage Patterns, ACM Transactions on Internet Technology, vol.3, issue.2, pp.93-116, 2003.

J. [. Chen, P. S. Park, and . Yu, Data Mining for Path Traversal Patterns in a Web Environment, Proceedings of the Sixteenth International Conference on Distributed Computing Systems, pp.385-392, 1996.

J. [. Chen, P. S. Park, and . Yu, Efficient data mining for path traversal patterns, IEEE Transactions on Knowledge and Data Engineering, vol.10, issue.2, pp.209-221, 1998.
DOI : 10.1109/69.683753

J. [. Cooley, B. Srivastava, and . Mobasher, Web mining: information and pattern discovery on the World Wide Web, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence, 1997.
DOI : 10.1109/TAI.1997.632303

L. [. Chen, O. Sun, R. Za¨?aneza¨?ane, and . Goebel, Visualizing and discovering web navigational patterns, Proceedings of the 7th International Workshop on the Web and Databases colocated with ACM SIGMOD/PODS 2004, WebDB '04, pp.13-18, 2004.
DOI : 10.1145/1017074.1017079

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.9117

B. [. Chelcea and . Trousse, Application of the 2-3 Agglomerative Hierarchical Classification on Web Usage Data, Proceedings of SYNASC 2004, Sixth International Workshop on Symbolic and Numeric Algorithms for Scientific Computing, pp.107-118, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00000289

P. [. Draier and . Gallinari, Characterizing Sequences of User Actions for Access Logs Analysis, Proceedings of the Eigth International Conference on User Modeling, pp.228-230, 2001.
DOI : 10.1007/3-540-44566-8_29

]. E. Did71 and . Diday, La méthode des nuées dynamiques, pp.19-34, 1971.

C. Sayed, E. A. Ruiz, and . Rundensteiner, FS-Miner: Efficient and Incremental Mining of Frequent Sequence Patterns in Web Logs, Proceedings of the Sixth Annual ACM International Workshop on Web Information and Data Management, pp.128-135, 2004.

P. [. Facca and . Lanzi, Mining interesting knowledge from weblogs: a survey, Data & Knowledge Engineering, vol.53, issue.3, pp.225-241, 2005.
DOI : 10.1016/j.datak.2004.08.001

G. [. Fayad, P. Piatetsky-shapiro, and . Smyth, From Data Mining to Knowldege Discovery: An Overview, Advances in Knowledge Discovery and Data Mining, pp.1-34, 1996.

K. [. Fu, M. Sandhu, and . Shih, A Generalization-Based Approach to Clustering of Web Usage Sessions, Proceedings of the 1999 KDD Workshop on Web Mining, pp.21-38
DOI : 10.1007/3-540-44934-5_2

]. A. Golli, B. Conan-guez, F. Rossi, D. Tanasa, B. Trousse et al., Les cartes topologiques auto-organisatrices pour l'analyse des fichiers logs, 11èmes Rencontre de la Société Francophone de Classification, pp.8-10, 2004.

K. [. Goldowitz and . Hamre, The cells and molecules that make a cerebellum, Trends in Neurosciences, vol.21, issue.9, pp.375-382, 1998.
DOI : 10.1016/S0166-2236(98)01313-7

]. A. Gia92 and . Giacometti, Modèles Hybrides de l'Expertise, 1992.

]. A. Gol04 and . Golli, Extraction de données symboliques et cartes topologiques : Application aux données ayant une structure complexe, 2004.

]. F. Gui04 and . Guillet, Mesure de la qualité des connaissances en ECD. Tutorial at EGC2004, Clermont Ferrand, 2004.

]. D. Gus97 and . Gusfield, Algorithms on Strings, Trees, and Sequences, 1997.

A. [. Huang, N. An, and . Cercone, Comparison of interestingness functions for learning web usage patterns, Proceedings of the eleventh international conference on Information and knowledge management , CIKM '02, pp.617-620, 2002.
DOI : 10.1145/584792.584896

]. J. Hbv04a, B. Huysmans, J. Baesens, and . Vanthienen, The Influence of Caching on Web Usage Mining, Proceedings of Data Mining 2004: the Fifth International Conference on Data Mining, Text Mining and their Business Applications, pp.15-17, 2004.

]. J. Hbv04b, B. Huysmans, J. Baesens, and . Vanthienen, Web Usage Mining: A Practical Study, Proceedings of the Twelfth Conference on Knowledge Acquisition and Management Kule (Poland), 2004.

M. [. Han and . Kamber, Data Mining, Concepts and Techniques, 2001.

H. [. Herder and . Weinreich, Interactive web usage mining with the navigation visualizer, CHI '05 extended abstracts on Human factors in computing systems , CHI '05, pp.1451-1454, 2005.
DOI : 10.1145/1056808.1056939

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.60.1067

G. [. Hay, K. Wets, and . Vanhoof, Discovering Interesting Navigation on a Web Site Using Sequence Alignment Method Extended with an Interestingness Measure, Proceedings of the Intelligent Techniques for Web Personalization, 2003.

]. M. Jac98 and . Jaczynski, Modèle et plate-formè a objets pour l'indexation des cas par situation comportementales: applicationàapplication`applicationà l'assistancè a la navigation sur le Web On Mining Web Access Logs, ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pp.63-69, 1998.

B. [. Jaczynski and . Trousse, WWW assisted browsing by reusing past navigations of a group of users, Proceedings of the Advances in Case-Based Reasoning, Forth European Workshop, EWCBR-98, pp.160-171, 1998.
DOI : 10.1007/BFb0056330

H. [. Kosala and . Blockeel, Web mining research, SIGKDD: SIGKDD Explorations: Newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining, ACM, pp.1-15, 2000.
DOI : 10.1145/360402.360406

T. [. Kagami and . Furuichi, Investigation of differentially expressed genes during the development of mouse cerebellum, Gene Expression Patterns, vol.1, issue.1, pp.39-59, 2001.
DOI : 10.1016/S1567-133X(01)00007-2

T. [. Kato, Y. Nakayama, and . Yamane, Navigation Analysis Tool Based on the Correlation Between Contets Distribution and Access Patterns, Worskhop on Web Mining for E-Commerce ? Challenges and Opportunities, pp.95-104, 2000.

]. T. Koh01 and . Kohonen, Self-Organizing Maps, 2001.

]. M. Kos and . Koster, The Web Robots Database

M. [. Kimball and . Ross, The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2002.

]. Kum04 and . Kum, ApproxMAP: Approximate Mining of Consensus Sequential Patterns, 2004.
DOI : 10.1137/1.9781611972733.36

S. [. Lipshutz, T. Fodor, D. Gingeras, and . Lockhart, High density synthetic oligonucleotide arrays, Nature Genetics, vol.21, issue.1, pp.20-24, 1999.
DOI : 10.1038/4447

C. [. Lewis and . Lewis, Suffix Trees in Computational Biology, 2003.

H. [. Lavoie and . Nielsen, Web Characterization Terminology & Definitions Sheet, 1999.

D. [. Lechevallier, B. Tanasa, R. Trousse, and . Verde, Classification automatique : Applications au Web Mining, Méthodes et Perspectives en Classification Presse Académiques Neuchâtel, pp.157-160, 2003.

R. [. Lechevallier and . Verde, Classiffication croisée d'un tableau de données symboliques : applicationàapplication`applicationà l'analyse du comportements des utilisateurs d'un site web, 11èmes Rencontre de la Société Francophone de Classification, pp.8-10, 2004.

[. Lee, R. Weindruch, and T. A. Prolla, Gene-expression Profile of the Aging Brain in Mice, Nature Genetics, vol.25, issue.3, pp.294-297, 2000.

]. M. Mal96 and . Malek, Un modèle hybride de mémoire pour le raisonnementàraisonnement`raisonnementà partir de cas, 1996.

M. Marco, Tecniche di classificazione di dati simbolici in un contesto di Web Usage Mining, 2004.

J. [. Mladenic, M. Brank, N. Grobelnik, and . Milic-frayling, Feature selection using linear classifier weights, Proceedings of the 27th annual international conference on Research and development in information retrieval , SIGIR '04, pp.234-241, 2004.
DOI : 10.1145/1008992.1009034

K. [. Marquardt, D. Becker, and . Ruiz, A pre-processing tool for web usage mining in the distance education domain, Proceedings. International Database Engineering and Applications Symposium, 2004. IDEAS '04., pp.78-87, 2004.
DOI : 10.1109/IDEAS.2004.1319780

R. [. Mobasher, J. Cooley, and . Srivastava, Automatic personalization based on Web usage mining, Communications of the ACM, vol.43, issue.8, pp.142-151, 2000.
DOI : 10.1145/345124.345169

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.7654

H. [. Mobasher, T. Dai, M. Luo, and . Nakagawa, Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization, Data Mining and Knowledge Discovery, vol.6, issue.1, pp.61-82, 2002.
DOI : 10.1023/A:1013232803866

. Mks-+-00-]-r, K. Matoba, S. Kato, C. Saito, C. Kurooka et al., Gene Expression in Mouse Cerebellum During Its Development, Gene, vol.241, issue.1, pp.125-131, 2000.

P. [. Masseglia, R. Poncelet, and . Cicchetti, An Efficient Algorithm for Web Usage Mining, Networking and Information Systems Journal (NIS), vol.2, pp.5-6571, 1999.

S. [. Maedche and . Staab, Ontology learning for the Semantic Web, IEEE Intelligent Systems, vol.16, issue.2, pp.72-79, 2001.
DOI : 10.1109/5254.920602

]. F. Mtp01a, M. Masseglia, P. Teisseire, and . Poncelet, Real Time Web Usage Mining: a Heuristic based Distributed Miner (long), Proceedings of the Web Information Systems Ingineering Conference (WISE'01), 2001.

]. F. Mtp01b, M. Masseglia, P. Teisseire, and . Poncelet, Web Usage Mining Inter- Sites : Analyse du comportement des utilisateursàutilisateurs`utilisateursà impact immédiat, 17 i` emes Journèes Bases de Données Avancées, 2001.

]. F. Mtt04a, D. Masseglia, B. Tanasa, and . Trousse, Diviser pour découvrir Une méthode d'analyse du comportement de tous les utilisateurs d'un site Web. RSTI -Ingénierie des systèmes d'information (ISI), pp.61-83, 2004.

]. F. Mtt04b, D. Masseglia, B. Tanasa, and . Trousse, Web Usage Mining: Sequential Pattern Extraction with a Very Low Support, Advanced Web Technologies and Applications: Proceedings of the Sixth Asia-Pacific Web Conference, pp.513-522, 2004.

R. [. Nasraoui and . Krishnapuram, AN EVOLUTIONARY APPROACH TO MINING ROBUST MULTI-RESOLUTION WEB PROFILES AND CONTEXT SENSITIVE URL ASSOCIATIONS, International Journal of Computational Intelligence and Applications, vol.02, issue.03, pp.339-348, 2002.
DOI : 10.1142/S1469026802000646

B. [. Oberle, A. Berendt, J. Hotho, and . Gonzalez, Conceptual User Tracking, Proceedings of Atlantic Web Intelligence Conference (AWIC'03), volume 2663 of LNAI, pp.155-164, 2003.
DOI : 10.1007/3-540-44831-4_17

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.7986

O. [. Perkowitz and . Etzioni, Adaptive Web sites, AAAI '98/IAAI '98: Proceedings of the Fifteenth National/Tenth International Conference on Artificial Intelligence/Innovative Applications of Artificial Intelligence, pp.727-732
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[. Pei, J. Han, B. Mortazavi-asl, and H. Zhu, Mining Access Patterns Efficiently from Web Logs, Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp.396-407, 2000.
DOI : 10.1007/3-540-45571-X_47

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.3204

M. [. Punin and . Krishnamoorthy, XGMML (eX- tensible Graph Markup and Modeling Language

. Ppk-+-00-]-g, C. Paliouras, V. Papatheodorou, P. Karkaletsis, C. D. Tzitziras et al., Large-Scale Mining of Usage Data on Web Sites, Proceedings of the AAAI Spring Symposium on Adaptive User Interfaces, pp.92-97, 2000.

Y. [. Rossi, A. Lechevallier, and . Golli, Visualisation de la perception d'un site web par ses utilisateurs. Revue des Nouvelles Technologies de l'Information (RNTI-E-3), numéro spécial EGC, pp.563-574, 2005.

R. [. Srikant and . Agrawal, Mining sequential patterns: Generalizations and performance improvements, Proceedings of the Fifth International Conference on Extending Database Technology (EDBT'96), pp.3-17, 1996.
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URL : http://arbor.ee.ntu.edu.tw/~chyun/dmpaper/srikms96.pdf

R. [. Silvestri, P. Baraglia, and . Palmerini, On-line generation of suggestions for Web users, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004., pp.104-108, 2004.
DOI : 10.1109/ITCC.2004.1286486

R. [. Srivastava, M. Cooley, P. Deshpande, and . Tan, Web usage mining, ACM SIGKDD Explorations Newsletter, vol.1, issue.2, pp.12-23, 2000.
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L. [. Spiliopoulou, K. Faulstich, and . Winkler, A Data Miner Analyzing the Navigational Behaviour of Web Users, Proceedings of the Workshop on Machine Learning in User Modelling of the ACAI'99 International Conference, 1999.

F. [. Shahabi and . Kashani, A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking, WEBKDD 2001 - Mining Web Log Data Across All Customers Touch Points, Third International Workshop, pp.113-144, 2001.
DOI : 10.1007/3-540-45640-6_6

]. M. Spi99 and . Spiliopoulou, Data Mining for the Web, Principles of Data Mining and Knowledge Discover, pp.588-589, 1999.

. Peter, R. Sneath, and . Sokal, Numerical Taxonomy: The Principles and Practice of Numerical Classification, 1973.

D. [. Santoni and . Tanasa, Construction de la structure logique d'un site web, 2003.

]. D. Tan02 and . Tanasa, Lessons from a Web Usage Mining Intersites Experiment, Proceedings of the First International Workshop on Data Cleaning and Preprocessing of the ICDM02, pp.99-107

J. [. Tanasa, B. López, and . Trousse, Extracting Sequential Patterns for Gene Regulatory Expressions Profiles, Knowledge Exploration in Life Science Informatics: International Symposium KELSI 2004, pp.46-57, 2004.
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B. [. Tanasa and . Trousse, Web Access Pattern Discovery and Analysis based on Page Classification and on Indexing Sessions with a Generalised Suffix Tree, Proceedings of the Third International Workshop on Symbolic and Numeric Algorithms for Scientific Computing, pp.62-72, 2001.

B. [. Tanasa and . Trousse, Le prétraitement des fichiers logs web dans le " Web Usage Mining " multi-sites, Journées Francophones de la Toile (JFT'2003), pp.113-122, 2003.

]. D. Tt04a, B. Tanasa, and . Trousse, Advanced Data Preprocessing for Intersites Web Usage Mining, IEEE Intelligent Systems, vol.19, issue.2, pp.59-65, 2004.

]. D. Tt04b, B. Tanasa, and . Trousse, Data Preprocessing for WUM, IEEE Potentials, vol.23, issue.3, pp.22-25, 2004.

]. D. Ttm04a, B. Tanasa, F. Trousse, and . Masseglia, Classer pour Découvrir : une nouvelle méthode d'analyse du comportement de tous les utilisateurs d'un site Web. Revue des Nouvelles Technologies de l'Information (RNTI), numéro spécial EGC, pp.549-560, 2004.

]. D. Ttm04b, B. Tanasa, F. Trousse, and . Masseglia, Mesures de l'internet, chapter Fouille de données appliquée aux logs web : ´ etat de l'art sur le Web Usage Mining Colloque " Mesures de l'internet, Les Canadiens en Europe, pp.126-143, 2003.

]. I. Tur02 and . Turner, The One-Stop Portal. Line56, 2002.

]. E. Ukk95 and . Ukkonen, On-line Construction of Suffix Trees, Algorithmica, vol.14, pp.249-260, 1995.

. J. Vbya04, A. Velásquez, H. Bassi, T. Yasuda, and . Aoki, Mining Web Data to Create Online Navigation Recommendations, Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM'04), pp.551-554, 2004.

[. Xiao and M. Dunham, Efficient mining of traversal patterns, Data & Knowledge Engineering, vol.39, issue.2, pp.191-214, 2001.
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R. [. Zhang, M. Ramakrishnan, and . Livny, BIRCH: An Efficient Data Clustering Method for Very Large Databases

M. [. Za¨?aneza¨?ane, J. Xin, and . Han, Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs, Proceedings of the Advances in Digital Libraries Conference, pp.19-29, 1998.