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2011611009
- 1. Top-k Approach ForCompact Storage Structure Guided By, Dr. Radha Senthilkumar By, S.Meenakshi, Assistant Professor 2011611009, Department of IT M.Tech I.T
- 2. Problem Definition Evaluatingthe tree edit distance for large xml trees is difficult. The best known xml algorithm have cubic run time and quadratic complexity is not scalable. A core problem is to efficiently prune sub trees.
- 3. Literature Survey cont… “Efficient Top-k Approximate Subtree Matchingin Small Memory “Nikolaus Augsten, Denilson Barbosa, Michael M. Bo¨ hlen, and Themis Palpanas, IEEE transactions on knowledge and data engineering, vol. 22, no. 8, August 2011. The top-k approximatec matches of a small query tree Q within a large document tree. Using prefix ring buffer that allows to efficiently prune subtrees. TASM is portable because it relies on the postorder queue structure which can be implemented by any xml processing that allows an efficient postorder traversal of trees.
- 4. Literature Survey cont… Jiaheng Lu, Pierre Senellart, Chunbin Lin, Xiaoyong Du, Shan Wang, Xinxing ChenMay “Optimal top-k generation of attribute combinations based on ranked lists” proc. ACM SIGMOD Int’l Conf. on Management of Data pp.1-12,2012. • A novel top-k query type, called top-k,m queries. • Suppose we are given a set of groups and each group contains a set of attributes, each of which is associated with a ranked list of tuples. • All lists are ranked in decreasing order of the scores of tuples. We want the top-k combinations of attributes according to the corresponding top-m tuples with matching IDs.
- 5. Literature Survey cont.. K.-C. Tai, “The Tree-to-Tree Correction Problem,” J. ACM, vol. 26,no. 3, pp. 422-433, 1979. • The string-to-string correction problem, which is to determine the distance between two strings as measured by the minimum cost sequence of edit operations needed to transform one string into the other. Three edit operations: changing one node of a tree into another node, deleting one node from a tree, or inserting a node into a tree; and they presented an algorithm that computes the distance between two strings in time O(m* n), where m and n are the lengths of the two given strings.
- 6. Objective To implementthe concept of dominating queries by the approach of Top-k Approximate Subtree Matching Problem. To evaluate the performance of dominating queries in the compact storage structure.
- 7. Dominating Queries Thenumber of result is controllable. The result is Scaling invariant. No user defined ranking function is requierd. Each point is assigned an intuitive score which determines its rank. TASM: • The problem of ranking the k best approximate matches of a small query tree in the large document tree.
- 8. References “Efficient Top-kApproximate Subtree Matchingin Small Memory “Nikolaus Augsten, Denilson Barbosa, Michael M. Bo¨ hlen, and Themis Palpanas, IEEE transactions on knowledge and data engineering, vol. 22, no. 8, August 2011. Jiaheng Lu, Pierre Senellart, Chunbin Lin, Xiaoyong Du, Shan Wang, Xinxing ChenMay “Optimal top-k generation of attribute combinations based on ranked lists” proc. ACM SIGMOD Int’l Conf. on Management of Data pp.1-12,2012. N. Augsten, M.H. Bo¨ hlen, C.E. Dyreson, and J. Gamper,“Approximate Joins for Data-Centric XML,” Proc. IEEE 24th Int’lConf. Data Eng. (ICDE), pp. 814-823, 2008. K.-C. Tai, “The Tree-to-Tree Correction Problem,” J. ACM, vol. 26,no. 3, pp. 422-433, 1979.
- 9. Timeline Chart PHASE REVIEW 1 REVIEW II REVIEW III Learning to work Implement the Evaluate the with TASM concept of dominating PHASE I (July) dominating queries in compact queries(August- storage structure September) ( October and November)
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