Abstract
As the explosive growth of online linked data, enormous RDF triples are produced every minute in various fields such as health, transportation, chemical, etc. There is an urgent need for an approach to finding and searching semantic association from massive data. However, the complex graph structure of the semantic association brings a great barrier to the process of searching. Transforming the complex graph into text-based structure is a better idea. To characterize the semantics of each association, a virtual document of each association is built with the help of a neighboring operation. A searching model of virtual documents of associations and a ranking schema are also discussed in this paper. Experiments show that our approach is feasible and efficient.
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References
Aleman-Meza, B., Halaschek-Wiener, C., Arpinar, I.B., Sheth, A.P.: Context-aware Semantic Association Ranking. In: Proceedings of the 1st International Workshop on Semantic Web and Databases, pp. 33–50 (2003)
Anyanwu, K., Sheth, A.: p-Queries: Enabling Querying for Semantic Associations on the Semantic Web. In: Proceedings of the 12th International World Wide Web Conference, pp. 690–699 (2003)
Kochut, K.J., Janik, M.: SPARQLeR: Extended Sparql for Semantic Association Discovery. In: Proceedings of the 4th European Conference on Semantic Web, pp. 145–159 (2007)
Zhang, X., Zhao, C., Wang, P., Zhou, F.: Mining Link Patterns in Linked Data. In: Gao, H., Lim, L., Wang, W., Li, C., Chen, L. (eds.) WAIM 2012. LNCS, vol. 7418, pp. 83–94. Springer, Heidelberg (2012)
Yan, X., Han, J.W.: gSpan: Graph-based Substructure Pattern Mining. In: Proceedings of the 2002 IEEE International Conference on Data Mining, pp. 721–724 (2002)
Le, B.T., Dieng-Kuntz, R., Gandon, F.: On Ontology Matching Problems - for Building a Corporate Semantic Web in a Multi-Communities Organization. In: Proceedings of the 2004 International Conference on Enterprize Information Systems, pp. 236–243 (2004)
Lacher, M.S., Groh, G.: Facilitating the Exchange of Explicit Knowledge through Ontology Mappings. In: Proceedings of the 14th Int. FLAIRS Conference, pp. 305–309 (2001)
Qu, Y., Hu, W., Cheng, G.: Constructing virtual documents for ontology matching. In: Proceedings of the 15th International Conference on World Wide Web (WWW 2006), pp. 23–31 (2006)
Doan, A., Madhavan, J., Dhamankar, R., Domingos, P., Halevy, A.Y.: Learning to Match Ontologies on the Semantic Web. Proceedings of the VLDB Journal 12(4), 303–319 (2003)
James, C.A., Weininger, D., Delany, J.: Daylight theory manual daylight version 4.82. Daylight Chemical Information Systems (2003)
Jiang, H., Wang, H., Yu, P.S., Zhou, S.: GString: A Novel Approach for Efficient Search in Graph Databases. In: Proceedings of IEEE 23rd International Conference on Data Engineering, ICDE, pp. 566–575 (2007)
Shasha, D., Wang, J.T., Giugno, R.: Algorithmics and applications of tree and graph searching. In: Proceedings of Symposium on Principle of Database Systems, PODS, pp. 39–52 (2002)
Yan, X., Yu, P.S., Han, J.: Substructure similarity search in graph databases. In: Proccedings of International Conference on Management of Data-SIGMOD, pp. 766–777 (2005)
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Wang, C., Zhang, X., Lv, Y., Ji, L., Wang, P. (2013). Searching Semantic Associations Based on Virtual Document. In: Qi, G., Tang, J., Du, J., Pan, J.Z., Yu, Y. (eds) Linked Data and Knowledge Graph. CSWS 2013. Communications in Computer and Information Science, vol 406. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54025-7_6
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DOI: https://doi.org/10.1007/978-3-642-54025-7_6
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