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

An Analysis of Keyword Search Retrieval Techniques on Multi-Dimensional Datasets

Author : Mrs. R.Ramya Devi ¹ T.Shanmuga Priya ²

Date of Publication :17th October 2017

Abstract: Information retrieval (IR) is the activity of obtaining information resources relevant to an information need from a collection of information resources. Searches can be based on full-text or other content-based indexing. Information retrieval is the most concentrated research field in the real world environment which enables users to retrieve the contents stored in the web. Keyword based search retrieval make ease of this task which can find the most similar information present web source accurate by computing similarity distance between the keywords submitted and the information present on web source. However keyword based similarity finding on multi-dimensional data would be more difficult task which required more computation to be performed. In this analysis work, comparison evaluation of different methodologies that are implemented to perform keyword based search retrieval on multi-dimensional data set has been discussed. Those research methodologies have been discussed based on their working procedures in detail. The different existing research methods are compared in detail based on their merits and demerits. The comparison analysis of research methods are conducted by comparing them with each other in terms of their merits and demerits. From this analysis, efficient research methodology that can perform key word based search retrieval in the flexible and accurate way can be identified in terms of performance improvement.

Reference :

1. Lakshmi, L., Reddy, P. B., Bindu, C. S., & Sri, S. B. (2017). An Effective nearest Keyword Search in Multifaceted Datasets. International Journal, 8(5).
2. Hristidis, V., & Papakonstantinou, Y. (2002, August). Discover: Keyword search in relational databases. In Proceedings of the 28th international conference on Very Large Data Bases (pp. 670-681). VLDB Endowment.
3. Z. Li, H. Xu, Y. Lu, and A. Qian, â€•Aggregate nearest keyword search in spatial databases,â€– in Asia-Pacific Web Conference, 2010.
4. I. De Felipe, V. Hristidis, and N. Rishe, â€•Keyword search on spatial databases,â€– in ICDE, 2008, pp. 656–665.
5. M. Datar, N. Immorlica, P. Indyk, and V. S. Mirrokni, â€•Locality-sensitive hashing scheme based on p-stable distributions,â€– in SCG, 2004
6. D. Zhang, Y. M. Chee, A. Mondal, A. K. H. Tung, and M. Kitsuregawa. Keyword search in spatial databases: Towards searching by document. In ICDE, pp. 688– 699, 2009
7. R. Hariharan, B. Hore, C. Li, and S. Mehrotra, “Processing Spatial- Keyword SK) Queries in Geographic Information Retrieval (GIR) Systems,” Proc. Scientific and Statistical Database Management (SSDBM), 2007.
8. Y.-Y. Chen, T. Suel, and A. Markowetz. Efficient query processing in geographic web search engines. In SIGMOD, pp. 277– 288, 2006.
9. X. Cao, G. Cong, and C. S. Jensen. Retrieving top-k prestige-based relevant spatial web objects. PVLDB, 3(1):373–384, 2010.
10. C. R. Barde, Pooja Katkade, Deepali Shewale and Rohit Khatale, “Secured Multiple-keyword Search over Encrypted Cloud Data ”,International Journal of Emerging Technology and Advanced Engineering , Volume 4, Issue 2, February 2014
11. C.Rajeshkumar and Dr.K.Rubasoundar, “Retrieval of Encrypted cloud data using multi-keyword”, International Journal of Innovative Research in Computer and Communication Engineering, Vol.2, Special Issue 1, March 2014.
12. K. Manoj Kumar, E. Purushotham, “Top-K Retrieval of Encrypted Cloud Data by Using Secure Multi-Keyword”, International Journal of Software and Hardware Research in Engineering, Vol 2,Issue 8, August 2014
13. Amol D. Sawant and Prof. M.D Ingle,” Indexing and Advanced Relevance Ranking Score Preserving for Multi Keyword Search over Encrypted Cloud Data”, International Journal of Computer Science and Information Technologies (IJCSIT), Vol. 5 (3),3165 – 3169,2014
14. Wenhai Sun, Bing Wang, Ning Cao, Ming Li, Wenjing Lou, Y. Thomas Hou and Hui Li, “Privacy-preserving Multi keyword Text Search in the Cloud Supporting Similarity based Ranking”, ASIA CCS, 2013
15. X. Cao, G. Cong, C.S. Jensen, and B.C. Ooi, “Collective Spatial Keyword Querying”, in Proc. ACM SIGMOD Intâ€Ÿl Conf. Management of Data, pp. 373- 384, 2011.
16. G. Cong, C.S. Jensen, and D. Wu, “Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects”, PVLDB, vol. 2, no. 1, pp. 337- 348, 2009.
17. R. Hariharan, B. Hore, C. Li, and S. Mehrotra, “Processing spatial-keyword (SK) queries in geographic information retrieval (GIR) systems”, in Proc. of Scientific and Statistical Database Management (SSDBM), 2007.
18. Yufei Tao and Cheng Sheng, “Fast Nearest Neighbor Search with Keywords”, IEEE transactions on knowledge and data engineering, VOL. 26, NO. 4, APRIL 2014.
19. Cao, Cong, G., and Jensen, C. S., “Retrieving top-k prestige based relevant spatial web objects”, PVLDB, 3(1), pp. 373– 384, 2010