Author : Adivikottu Ramakrishna 1
Date of Publication :6th June 2017
Abstract: A customer who has issued a Query word question to a web searcher. The Keyword proposals are the most important element of the web search tool. Truthful clients don't know how to express their examination accurately more often than not questions are short and unambiguous. Using that watchwords web file recovers the reports, the proposed Query hold phrase inquiries to the customer, which are semantically noteworthy to the main question and they have results records that contrast with objects near the customer's region. Thus, here propose a weighted Keyword-Query record graph which gets semantic likewise, expel among inquiries and reports. By then, use the outline to propose questions that are shut as far as graph detachment to the primary inquiries. Fragment-based estimation is used to make the structure more flexible, using the proposed take hold of phrases the system again performs watchword controlling. In catchphrase guiding, the system removes all the keep words from the sentence. By then form a candidate question graph, to find the base partition between the segments. Least Crossing tree is used to find the partition between the segments
Reference :
-
- Cong Wang, Student Member, IEEE, Ning Cao, Student Member, IEEE, Kui Ren, Senior Member, IEEE, Wenjing Lou, Senior Member, IEEE, “Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data”, IEEE Transactions on Parallel and Distributed Systems Vol.23 No.8 Year 2012.
- C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure ranked keyword search over encrypted cloud data,” in Proc. of ICDCS’10, 2010
- P. Mell and T. Grance, “Draft nist working definition of cloud computing,” Referenced on Jan. 23rd, 2010 online at http:/ csrc. nist.gov/groups/SNS/cloudcomputing/ index. html, 2010.
- M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, “A view of cloud computing,” Commun. ACM, vol. 53, no. 4, pp. 50–58, 2010.
- C. Wang, S. S. Chow, Q. Wang, K. Ren, and W. Lou, “Privacy-preserving public auditing for secure cloud storage,” IEEE Trans. Comput., vol. 62, no. 2, pp. 362– 375, Feb. 2013.
-
- Peter mell, Timothy Grance, NIST definition of Cloud Computing, NIST special publication 800- 145.
- Alexa Huth and James Cebula(2011), “ The basics of cloud xomputing”.
- Semantic web, https : // en . wikipedia . org / wiki / Semantic _ Web, accessed 12th june 2015.
- Semantic web stack, https: //en .wikipedia. org/ wiki/ Semantic_Web_Stack, accessed 4th april 2016.
- Resource Description Framework, https://en.wikipedia.org/wiki/Resource_Descripti on_Framework, accessed 3rd march 2015.
-
- D. Beeferman and A. Berger, “Agglomerative clustering of a search engine query log,” in Proc. 6th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, 2015, pp. 407–416.
- U. Ozertem, O. Chapelle, P. Donmez, and E. Velipasaoglu, “Learning to suggest: A machine learning framework for ranking query suggestions,” in Proc. 35th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2014, pp. 25–34.
- H. Cao, D. Jiang, J. Pei, Q. He, Z. Liao, E. Chen, and H. Li, “Context-aware query suggestion by mining clickthrough and session data,” in Proc. 14th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, 2013, pp. 875– 883.
- N. Craswell and M. Szummer, “Random walks on the click graph,” in Proc. 30th Annu. Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2012, pp. 239–246.
- Y. Song and L.-W. He, “Optimal rare query suggestion with implicit user feedback,” in Proc. 19th Int. Conf. World Wide Web, 2012, pp. 901–910.