Survey on Nearest Keyword Set Search in Multi-dimensional Datasets

A. Jebamalar, Anbuselvi Anbuselvi

Abstract


Keyword query in multi-dimensional datasets is a noteworthy application in information mining. It is normal that the articles in a spatial database (e.g. eateries/inns) are connected with keyword(s) to demonstrate their organizations/administrations/highlights. An interesting issue known as neighboring Keywords inquiry is to question objects, called catchphrase cover, which together cover an agreement of question watchwords and have the base among items remove. As of late, we watch the increasing accessibility and significance of catchword rating in protest assessment for the better basic leadership. This propels us to study a non-particular version of Closest Keywords search called Best Keyword Cover which considers among items remove and also the watchword evaluation of articles. The baseline algorithm is enlivened by the strategies for Closest Keywords search which depends on comprehensively joining objects from various query keywords to produce contestant catchphrase covers. At the point when the quantity of query keywords builds, the execution of the baseline algorithm drops extensively as a consequence of enormous competitor catchphrase covers produced. To assault this downside, this work proposes an a great deal more adaptable algorithm called catchphrase nearest neighbor expansion (watchword NNE). Contrasted with the baseline algorithm, watchword NNE algorithm fundamentally decreases the amount of applicant catchphrase covers formed. The surrounded by and out investigation and broad examinations on genuine information sets have legitimized the prevalence of our watchword NNE algorithm.

Full Text:

PDF

References


Li, Zhisheng, Ken CK Lee, Baihua Zheng, Wang-Chien Lee, Dik Lee, and Xufa Wang. "Ir-tree: An efficient index for geographic document search." IEEE Transactions on Knowledge and Data Engineering 23, no. 4 (2011): 585-599.

Cao, Xin, Gao Cong, and Christian S. Jensen. "Retrieving top-k prestige-based relevant spatial web objects." Proceedings of the VLDB Endowment 3, no. 1-2 (2010): 373-384.

Cong, Gao, Christian S. Jensen, and Dingming Wu. "Efficient retrieval of the top-k most relevant spatial web objects." Proceedings of the VLDB Endowment 2, no. 1 (2009): 337-348.

Basu Roy, Senjuti, and Kaushik Chakrabarti. "Location-aware type ahead search on spatial databases: semantics and efficiency." In Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, pp. 361-372. ACM, 2011.

Zhang, Dongxiang, Beng Chin Ooi, and Anthony KH Tung. "Locating mapped resources in web 2.0." In Data Engineering (ICDE), 2010 IEEE 26th International Conference on, pp. 521-532. IEEE, 2010.

Ashlesh S. Patole; Shripadrao Biradar “ A Survey on Best Keyword Cover Search “ IJIRCCE Vol. 3, Issue 11, November 2015 ISSN(Online): 2320-9801 ISSN (Print): 2320-9798

Ke Deng; Xin Li; Jiaheng Lu; Xiaofang Zhou,” Best Keyword Cover Search” Knowledge and Data Engineering, IEEE Transactions on Year: 2015.


Refbacks

  • There are currently no refbacks.




© International Journals of Advanced Research in Computer Science and Software Engineering (IJARCSSE)| All Rights Reserved | Powered by Advance Academic Publisher.