Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Fuzzy Ontology Model for Gathering Web Information

Author : Sayali Dharmendra Behere 1 R. B. Wagh 2

Date of Publication :7th August 2016

Abstract: A model for knowledge description and formalization, these various on tologies are widely used to represent various user profiles in personalized web information gathering manner. Represent these user profiles, many of these models have evaluate only their knowledge from either a global knowledge base, and also it called as a user local information. In this paper, a Fuzzy is a semi-automated collaborative tool for the construction of fuzzy ontology models. Fuzzy is an extension of the well known ontology model for which we have defined new meta classes to allow the definition of parameterized functions. Fuzzy also gives support to instantiate fuzzy concepts and roles. Fuzzy allows querying fuzzy ontologies based on fuzzy criteria. We present in this paper the Fuzzy Ontology Algorithm for gathering web related information we give some details on its implementation and also the way we use it to validate fuzzy ontologism.

Reference :

    1. X. Jiang and A.-H. Tan, “Mining Ontological Knowledge from Domain-Specific Text Documents”, in the proceedings of Fifth IEEE Int‟l Conf. Data Mining (ICDM „05), pp. 665-668, 2005.
    2. Y. Li and N. Zhong, “Mining Ontology for Automatically Acquiring Web User Information Needs”, IEEE Trans. Knowledge and Data Eng., vol. 18, No. 4, pp. 554–568, Apr. 2006.
    3. N. Zhong, “Representation and Construction of Ontologies for Web Intelligence”, Int‟l J Foundation of Computer Science, vol. 13, No. 4, pp. 1-14, 2003.
    4. Y. Li and N. Zhong, “Web Mining Model and its Application for Information Gathering”, Knowledge Based Systems, Vol. 17, pp. 207-211, 2004.
    5. J. Trajkova and S. Gauch, “Improving Ontology-Based User Profiles” in Proc. Conf. Rescherche d‟Information Assistee par Ordinateur(RIAO‟04), pp. 380-389, 2004.
    6. W. Jin, R.K. Srihari, H.H. Ho, and X. Wu, “Improving knowledge Discovery in Document Collections through Combining Text Retrieval and Link Analysis Techniques”, in Proc. Seventh IEEE Int‟l Conf. Data Mining(ICDM‟07), pp. 193-202, 2007.
    7. R. Navigli, P. Velardi, and A. Gangemi, “Ontology Learning and it‟s Application to automated Terminology Translation”, IEEE Intelligent Systems, vol. 18, no. 1, pp. 22-31, Jan/Feb 2003.
    8. A. Sieg, B. Mobasher, and R. Burke, “Web Search Personalization with Ontological User profiles”, in Proc. Of the 16th ACM conf. Information and knowledge Management (CIKM „07), pp. 525-534, 2007.
    9. S. Shehata, F. Karray, and M. Kamel, “Enhancing Search Engine quality Using Concept-Based Text Retrieval”, in Proc. IEEE/WIC/ACM Int‟l Conf. Web Intelligence (WI „07), pp. 26-32,2007
    10. R.Y.K. Lau, D. Song, Y. Li, C.H. Cheung, and J. X. Hao, “Towards a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning”, IEEE Trans. Knowledge and Data Eng., Vol. 21, No. 6, pp. 800-813, June 2009.
    11. A. Doan, J. Madhavan, P. Domingos, and A. Halevy, “Learning to Map between Ontologies on the Semantic Web”, Proc. 11th Int‟l Conf. World Wide Web (WWW „02), pp. 662-673, 2002
    12. K. van der Sluijs and G.J. Huben, “Towards a Generic User Model Component”, Proc. Workshop Personalization on the Semantic Web Conf. (PerSWeb „05), 10th Int‟l Conf. User Modeling (UM „05), pp. 43-52, 2005.
    13. P.A. Chirita, C.S. Firan, and W. Nejdl,“Personalized Query Expansion for the Web”, Proc. ACM SIGIR („07), pp. 7-14, 2007
    14. J. Han and K.C.-C. Chang, “Data Mining for Web Intelligence”, Computer, Vol. 35, No. 11, pp. 64-70, Nov. 2002.
    15. Y. L. Xiaohui Tao and S. M. Ning Zhong, “A Personalized Ontology Model for Web Information Gahtering, in the proceedings of IEEE Transactions on Knowledge and Data Engineering, Vol. 23, pp. 496-511, April. 2011.

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