Abstract
KSORD(Keyword Search Over Relational Databases) is an easy and effective way for casual users or Web users to access relational databases. In recent years, much research on KSORD has been done, and many prototypes of KSORD have been developed. However, there are still critical problems on the efficiency and effectiveness of KSORD systems. In this paper, we describe the overview of KSORD research and development, analyze the efficiency and effectiveness problems in existing KSORD systems, and introduce our study on KSORD in terms of efficiency and effectiveness. In the end, we point out the emerging topics worthy of further research in this area.
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References
Wang, S., Zhang, K.: Searching Databases with Keywords. Journal of Computer Science and Technology 20(1), 55–62 (2005)
Qi, S., Jennifer, W.: Indexing Relational Database Content Offline for Efficient Keyword-Based Search. In: IDEAS, pp. 297–306 (2005)
Balmin, A., Hristidis, V., Papakonstantinou, Y.: ObjectRank: Authority-Based Keyword Search in Databases. In: VLDB, pp. 564–575 (2004)
Zhan, J., Wang, S.: ITREKS: Keyword Search over Relational Database by Indexing Tuple Relationship. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 67–78. Springer, Heidelberg (2007)
Wen, J., Wang, S.: SEEKER: Keyword-based Information Retrieval Over Relational Data-bases (in Chinese). Journal of Software 16(4), 540–552 (2005)
Agrawal, S., Chaudhuri, S., Das, G.: DBXplorer: A System for keyword Search over Relational Databases. In: ICDE, pp. 5–16 (2002)
Hristidis, V., Papakonstantinou, Y.: DISCOVER: Keyword Search in Relational Databases. In: VLDB, pp. 670–681 (2002)
Hristidis, V., Gravano, L., Papakonstantinou, Y.: Efficient IR-Style Keyword Search over Relational Databases. In: VLDB, pp. 850–861 (2003)
Bhalotia, G., Hulgeri, A., Nakhe, C., et al.: Keyword Searching and Browsing in Databases using BANKS. In: ICDE, pp. 431–440 (2002)
Kacholia, V., Pandit, S., Chakrabarti, S., et al.: Bidirectional Expansion For Keyword Search on Graph Databases. In: VLDB, pp. 505–516 (2005)
Wang, S., Peng, Z., Zhang, J., et al.: NUITS: A Novel User Interface for Efficient Keyword Search over Databases. In: VLDB, pp. 1143–1146 (2006)
Ding, B., Yu, J., Wang, S., et al.: Finding Top-k Min-Cost Connected Trees in Databases. In: ICDE (2007)
Randall, K.H., Stata, R., Wickremesinghe, R., Wiener, J.L.: The link database: Fast access to graphs of the web. In: The Data Compression Conference, pp. 122–131 (2002)
Liu, F., Yu, C., Meng, W., Chowdhury, A.: Effective Keyword Search in Relational Databases. In: SIGMOD, pp. 563–574 (2006)
Wheeldon, R., Levene, M., Keenoy, K.: DbSurfer: A Search and Navigation Took for Relational Databases. In: 21st Annual British National Conference on Databases, pp. 144–149 (2004)
Dar, S., et al.: DTL’s DataSpot:Database Exploration Using Plain Language. In: VLDB (1998)
Das, S., Chong, E.I., Eadon, G., Srinivasan, J.: Supporting Ontology-Based Semantic matching in RDBMS. In: VLDB, pp. 1054–1065 (2004)
Ranganathan, A., Liu, Z.: Information Retrieval from Relational Databases using Semantic Queries. In: CIKM, pp. 820–821 (2006)
Zhang, J., Peng, Z., Wang, S., Nie, H.: Si-SEEKER: Ontology-Based Semantic Search over Databases. In: Lang, J., Lin, F., Wang, J. (eds.) KSEM 2006. LNCS (LNAI), vol. 4092, pp. 599–611. Springer, Heidelberg (2006)
Ganesan, P., Garcia-Molina, H., Widom, J.: Exploiting Hierarchical Domain Structure to Compute Similarity. ACM Trans. Inf. Syst. 21(1), 64–93 (2003)
Zhang, J., Peng, Z., Wang, S., Nie, H.: PreCN: Preprocessing Candidate Networks for Efficient Keyword Search over Databases. In: Aberer, K., Peng, Z., Rundensteiner, E.A., Zhang, Y., Li, X. (eds.) WISE 2006. LNCS, vol. 4255, pp. 28–39. Springer, Heidelberg (2006)
Zhang, K.: Research on New Preprocessing Technology for Keyword Search in Databases. PhD thesis (in Chinese) of Renmin University of China (2005)
Peng, Z., Zhang, J., Wang, S., Qin, L.: TreeCluster: Clustering Results of Keyword Search over Databases. In: Yu, J.X., Kitsuregawa, M., Leong, H.-V. (eds.) WAIM 2006. LNCS, vol. 4016, pp. 385–396. Springer, Heidelberg (2006)
Zhang, J., Peng, Z., Wang, S., Nie, H.: CLASCN: Candidate Network Selection for Efficient Top-k Keyword Queries over Databases. Journal of Computer Science and Technology 22(2), 197–207 (2007)
Baeza-Yates, R., Ribeiro-Neto, B., et al.: Modern Information Retrieval, pp. 27–30. ACM Press, New York (1999)
Zhang, J., Peng, Z., Wang, S.: QuickCN: A Combined Approach for Efficient Keyword Search over Databases. In: Kotagiri, R., Radha Krishna, P., Mohania, M., Nantajeewarawat, E. (eds.) DASFAA 2007. LNCS, vol. 4443, pp. 1032–1035. Springer, Heidelberg (2007)
Zhang, J., Peng, Z., Wang, S., Zhan, J.: Exploiting Connection Relation to Compress Data Graph. In: Chang, K.C.-C., Wang, W., Chen, L., Ellis, C.A., Hsu, C.-H., Tsoi, A.C., Wang, H. (eds.) APWeb/WAIM 2007. LNCS, vol. 4537, pp. 241–246. Springer, Heidelberg (2007)
Sayyadian, M., LeKhac, H., Doan, A., Gravano, L.: Efficient Keyword Search Across Heterogeneous Relational Databases. In: ICDE (2007)
Voorhees, E.M., Harman, D.K.: Overview of the 6th Text REtrieval Conference (TREC-6). In: Proceedings of the 6th Text REtrieval Conference (1997)
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Wang, S., Zhang, J., Peng, Z., Zhan, J., Wang, Q. (2007). Study on Efficiency and Effectiveness of KSORD. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_5
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DOI: https://doi.org/10.1007/978-3-540-72524-4_5
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