On the other hand. table 9 H. Analysis of multiple evidence satisfaction revealed by the users about the Proceedings of the 20th ACM Int. Conference on Research and the collaborative modules evIdence and Development in IR (SIGIR'97). New York, 1997 [10]Lozano-Tel Table 9. Average satisfactions values(1-5 rating scale) for ontologies lethod to choose the appropriate ontology. Journal of reused in tasks 2 and 3, collaborative recommendations and rankings Task 2 Task Initial term Final ontology [11]Maedche, A, and Staab, S. Measuring similarity between vement ontologies. Proceedings of the 13th European Conference on Knowledge Acquisition and Management(EKAW 2002 Madrid, Spain, 2002 5 CONCLUSIONS AND FUTURE WORK [12 Miller, G.A. WordNet: A lexical database for English.Neww In this paper, a web application for ontology evaluation and horizons in commercial and industrial Artificial intelligence has been presented. The novel aspects of our proposal include the Communications of the Association for Computing use of WordNet to help users to define the Golden Standard; a Machinery,38(11):39-41,1995. new ontology retrieval technique based on traditional Information [13]Montaner, M, Lopez, B, and De la Rosa, J. L. A Taxonomy Retrieval models; rank fusion techniques to combine different of Recommended Agents on the Internet. Artificial ntology evaluation measures, and two collaborative modules intelligence Review 19: 285-330. 2003 one that suggests the most popular terms for a given domain, and one that recommends lists of ontologies with a multi-criteria [14]Noy, N. F, Chugh, A, Liu, W,and Musen,M.A:A strategy that takes into account user opinions about ontology Framework for Ontology Evolution in Collaborative features that can only be assessed by humans. Environments. Proceedings of the 5th Int. Semantic Web Conference(ISwC06) Athens, Georgia, USA, 2006 6. ACKNOWLEDGMENTS [15 Paslaru, E. Using Context Information to Improve Ontolog ah reseatico was zopo ed s th punish Mamistry of scienc euse. Doctoral Workshop at the 17th Conference on Advanced Information Systems Engineering(CAISEO 7. REFERENCES [1 Adomavicius, G, and Tuzhilin, A Toward the Nex [16 Porzel, R, and Malaka, R. A task Generation of Recommender Systems: A Survey of the State on Artificial Intelligence(ECAl'04). Valencia, Spain, 200c ontology evaluation. Proc. of the 16th European Conferenc of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering 17(6): 734-749, 2005 [17] Protege OWL ontology Repository [2 Alani, H, and Brewster, C. Metrics for Ranking Ontologies ings of the 4th Int. Workshop on Evaluation of [18]Resnick, P, lacovo, N, Suchak, M, Bergstrom, P, and gies for the Web(eon06), at the 15th Int. World roupLens: An Open Architecture for eb Conference(www06). Edinburgh, UK, 2006 Collaborative Filtering of Netnews. Internal Research [3 Ontologies with AKTiveRank.Proc.of the Sth IntSemantic Report, MIT Center for Coordination Science, 1994 ani, H, Brewster, C and Shadbolt, N. Ranking [19] Sabo V Web Conference(ISwC06). Athens, Georgia, USA, 2006 on the Real semantic Web. Proceedings [4 Brank J, Grobelnik M, and Mladenic D A Survey of shop on Evaluation of Ontologies for at the 15th Int. world wide Web Ontology Evaluation Techniques. Proceedings of the 4th Conference on Data Mining and Data Warehouses www 06). Edinburgh, UK, 2006 iKDD.05), at the 7th Int Multi-conference on Information 1., Lopez, V, Motta, E, and Uren, V: Ontology Society(Is'05) Ljubljana, Slovenia, 2005 for the Real Semantic Web: How to cover the 5 Brewster, C, Alani, H, Dasmahapatra, Sand Wilks, YData Birthday Dinner? Proc. of the 15th International driven ontology evaluation. Proc. of the 4th Int. Conf.on Conference on Knowledge Engineering and Knowledge Language Resources and Evaluation(LRECO4) Lisbon 2004 Management(EKAw06) Podebrady, Czech Republic, 2006 [6 Ding, Y, and Fensel, D. Ontology Library Systems: The key to 21 Salton, G, and McGill, M: Introduction to Modern Information Retrieval. McGraw-Hill, New York, 1983 Working Symposium(Swws'O1) Stanford, CA, USA, 2001 22 mip,l a o Atomig: Folksonomy: Social Classification. 2004 7 Farquhar, A, Fikes, R, and Rice, J. The Ontolingua server: tomi. org/archives/2004/08/folksonomy_ social class A tool for collaborative ontology construction. Technical report, Stanford KSL 96-26, 1996 [23] Erdmann, M, Angele, J, Staab, S, Studer, R, and 18 Fernandez, M, Cantador, I, and Castells, P CORE. A Tool D: OntoEdit: Collaborative Ontology Development for the Semantic Web. Proceedings of the lst International for Collaborative Ontology Reuse and evaluation Proceedings of the 4th Int. Workshop on Evaluation of Semantic Web Conference(IS"02), Sardinia, Italy, 2002 Ontologies for the Web(EON06), at the 15th Int. Worl 24 Swoogle- Semantic Web Search Engine Wide Web Conference(www06) Edinburgh, UK, 2006 http://swoogle.umbc.eduOn the other hand, table 9 shows the average degrees of satisfaction revealed by the users about the retrieved ontologies and the collaborative modules. Again, the results evidence positive applications of our approach. Table 9. Average satisfactions values (1-5 rating scale) for ontologies reused in tasks 2 and 3, collaborative recommendations and rankings Task 2 Task 3 % improvement Initial term recommendation Final ontology ranking 3.34 3.56 6.58 4.7 4.4 5. CONCLUSIONS AND FUTURE WORK In this paper, a web application for ontology evaluation and reuse has been presented. The novel aspects of our proposal include the use of WordNet to help users to define the Golden Standard; a new ontology retrieval technique based on traditional Information Retrieval models; rank fusion techniques to combine different ontology evaluation measures; and two collaborative modules: one that suggests the most popular terms for a given domain, and one that recommends lists of ontologies with a multi-criteria strategy that takes into account user opinions about ontology features that can only be assessed by humans. 6. ACKNOWLEDGMENTS This research was supported by the Spanish Ministry of Science and Education (TIN2005-06885 and FPU program). 7. REFERENCES [1] Adomavicius, G., and Tuzhilin, A.: Toward the Next Generation of Recommender Systems: A Survey of the State￾of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering 17(6): 734-749, 2005. [2] Alani, H., and Brewster, C.: Metrics for Ranking Ontologies. Proceedings of the 4th Int. Workshop on Evaluation of Ontologies for the Web (EON’06), at the 15th Int. World Wide Web Conference (WWW’06). Edinburgh, UK, 2006. [3] Alani, H., Brewster, C., and Shadbolt, N.: Ranking Ontologies with AKTiveRank. Proc.. of the 5th Int. Semantic Web Conference (ISWC’06). Athens, Georgia, USA, 2006. [4] Brank J., Grobelnik M., and Mladenic D.: A Survey of Ontology Evaluation Techniques. Proceedings of the 4th Conference on Data Mining and Data Warehouses (SiKDD‘05), at the 7th Int. Multi-conference on Information Society (IS’05). Ljubljana, Slovenia, 2005. [5] Brewster, C., Alani, H., Dasmahapatra, S. and Wilks, Y. Data driven ontology evaluation. Proc. of the 4th Int. Conf. on Language Resources and Evaluation (LREC04). Lisbon 2004 [6] Ding, Y., and Fensel, D.: Ontology Library Systems: The key to successful Ontology Reuse. Proc. of the 1st Semantic Web Working Symposium (SWWS’01). Stanford, CA, USA, 2001. 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New horizons in commercial and industrial Artificial Intelligence. Communications of the Association for Computing Machinery, 38(11): 39-41, 1995. [13]Montaner, M., López, B., and De la Rosa, J.L.: A Taxonomy of Recommended Agents on the Internet. Artificial intelligence Review 19: 285-330, 2003. [14] Noy, N. F., Chugh, A., Liu, W., and Musen, M. A.: A Framework for Ontology Evolution in Collaborative Environments. Proceedings of the 5th Int. Semantic Web Conference (ISWC’06). Athens, Georgia, USA, 2006. [15] Paslaru, E.: Using Context Information to Improve Ontology Reuse. Doctoral Workshop at the 17th Conference on Advanced Information Systems Engineering (CAiSE’05). Porto, Portugal, 2005. [16] Porzel, R., and Malaka, R.: A task-based approach for ontology evaluation. Proc. of the 16th European Conference on Artificial Intelligence (ECAI’04). Valencia, Spain, 2004. [17]Protégé OWL ontology Repository. http://protege.stanford.edu/download/ontologies.html [18]Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., and Riedl, J.: GroupLens: An Open Architecture for Collaborative Filtering of Netnews. Internal Research Report, MIT Center for Coordination Science, 1994. [19] Sabou, M., López, V., Motta, E., and Uren, V.: Ontology Evaluation on the Real Semantic Web. Proceedings of the 4th Int. Workshop on Evaluation of Ontologies for the Web (EON’06), at the 15th Int. World Wide Web Conference (WWW’06). Edinburgh, UK, 2006. [20] Sabou, M., López, V., Motta, E., and Uren, V.: Ontology Selection for the Real Semantic Web: How to cover the Queen’s Birthday Dinner? Proc. of the 15th International Conference on Knowledge Engineering and Knowledge Management (EKAW’06). Podebrady, Czech Republic, 2006. [21] Salton, G., and McGill, M.: Introduction to Modern Information Retrieval. McGraw-Hill, New York, 1983. 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