Top-N Query Processing


The objective of this project is to develop techniques for the efficient evaluation of top-N queries. A top-N query returns the N results that satisfy the query condition the best but not necessarily completely. Satisfaction of the result with respect to a query is measured by the distance between the tuple and the query based on some distance function.


Related publications

  1. Weiyi Meng, Clement Yu, Wei Wang, Naphtali Rishe: Performance Analysis of Several Algorithms for Processing Joins between Textual Attributes. Proc. of the 12-th IEEE International Conference on Data Engineering, pp.636-644, New Orleans, Louisiana, February 1996.
  2. Weiyi Meng, Clement Yu, Wei Wang, Naphtali Rishe: Performance Analysis of Three Text-Join Algorithms. IEEE Transactions on Knowledge and Data Engineering. Vol.10, No.3, pp.477-492, May/June 1998.
  3. Changqin Zhang, Weiyi Meng, Zhongfei Zhang, Zonghuan Wu. WebSSQL - A Query Language for Multimedia Web Documents . IEEE Conference on Advances in Digital Libraries (ADL'00), Washington, D.C., May 2000.
  4. Clement Yu, Prasoon Sharma, Weiyi Meng, and Yan Qin. Database Selection for Processing k Nearest Neighbors Queries in Distributed Environments , First ACM/IEEE Joint Conference on Digital Libraries, Roanoke, VA, June 2001, pp.215-222.
  5. Yuxi Chen, and Weiyi Meng. Top-N Query: Query Language, Distance Function and Processing Strategies. . Proc. of Fourth International Conference on Web-Age Information Management (WAIM'03), pp.459-470, Chengdu, China, August 2003.
  6. Clement Yu, George Philip, Weiyi Meng. Distributed Top-N Query Processing with Possibly Uncooperative Local Systems . Proc. of 29th International Conference on Very Large Data Bases (VLDB'03), pp.117-128, Berlin, Germany, September 2003.
  7. Liang Zhu, and Weiyi Meng. Learning-Based Top-N Selection Query Evaluation over Relational Databases. Fifth International Conference on Web-Age Information Management (WAIM'04), Lecture Notes in Computer Science, (copyright Springer-Verlag, http://www.springer.de/com/lncs/index.html), pp.197-207, Dalian, China, July 2004.
  8. Liang Zhu, Weiyi Meng, Wenzhu Yang, Chunnian Liu. Region Clustering Based Evaluation of Multiple Top-N Selection Queries. International Journal of Data & Knowledge Engineering, Vol.64, No.2, pp.439-461, February 2008.
  9. Liang Zhu, Weiyi Meng, Chunnian Liu, Wenzhu Yang, Dazhong Liu. Processing Top-N Relational Queries by Learning. Journal of Intelligent Information Systems, Vol.34, No.1, pp.21-55, February 2010.
  10. Liang Zhu, Qin Ma, Weiyi Meng, Mingqian Yang, and Fang Yuan. An Experimental Evaluation of Aggregation Algorithms for Processing Top-K Queries. 15th IEEE International Conference on Computer and Information Technology (CIT-2015), pp.326-333, Liverpool, England, UK, October 2015
  11. Liang Zhu, Feifei Liu, Weiyi Meng, Qin Ma, Yu Wang, and Fang Yuan. Evaluating Top-N Queries in n-Dimensional Normed Spaces. Information Sciences (to appear)

Last change: September 15, 2016 / meng@cs.binghamton.edu