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Hierarchical Data Summarization

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Hierarchical data summarization

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Given a set of records data summaries on different attributes are frequently produced in data management systems. Commonly used examples are the number of records that fall into a set of ranges of an attribute or the minimum values in these ranges. To improve the efficiency in accessing summaries at different resolutions or due to a direct need for investigating a hierarchy that is inherent to the data type, such as dates, hierarchical versions of data summaries can be used. A data structure or algorithm is labelled as hierarchical if that structure or algorithm uses the concept of subcomponents to systematically obtain conceptually larger components. The method of obtaining a larger component is regularly induced by the user’s understanding of the domain, such as dates in a year, as well as the fact that hierarchies can also be created automatically by a set of rules embedded into the system. Thus, rules used in a data structure’s...

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  1. Aboulnaga A. and Aref W.G. Window query processing in linear quadtrees. Distrib. Parallel Dat., 10(10):111–126, 2001.

    Article  MATH  Google Scholar 

  2. Ali M.E., Zhang R., Tanin E., and Kulik L. 2008, A motion-aware approach to continuous retrieval of 3D objects. In Proc. 24th Int. Conf. on Data Engineering, pp. 843–852.

    Google Scholar 

  3. Antoshenkov G. Query processing in DEC RDB: major issues and future challenges. IEEE Data Eng. Bull., 16(4):42–45, 1993.

    Google Scholar 

  4. Aoki P.M. Generalizing “search” in generalized search trees. In Proc. 14th Int. Conf. on Data Engineering, 1998, pp. 380–389.

    Google Scholar 

  5. Bruno N., Chaudhuri S., and Gravano L. STHoles: a multidimensional workload-aware histogram. ACM SIGMOD Rec., 30(2):211–222, 2001.

    Article  Google Scholar 

  6. Ganesan D., Estrin D., and Heidemann J. DIMENSIONS: why do we need a new data handling architecture for sensor networks? In Proc. ACM Workshop on Hot Topics in Networks, 2002.

    Google Scholar 

  7. Gao J., Guibas L.J., Hershberger J., and Zhang L. Fractionally cascaded information in a sensor network. In Proc. 3rd Int. Symp. Inf. Proc. in Sensor Networks, 2004, pp. 311–319.

    Google Scholar 

  8. Greenstein B., Estrin D., Govindan R., Ratnasamy S., and Shenker S. DIFS: a distributed index for features in sensor networks. In Proc. IEEE Int. Workshop on Sensor Network Protocols and Applications, 2003, pp. 163–173.

    Google Scholar 

  9. Hellerstein J.M., Naughton J.F., and Pfeffer A. Generalized search trees for database systems. In Proc. 21th Int. Conf. on Very Large Data Bases, 1995, pp. 562–573.

    Google Scholar 

  10. Knuth D.E. Sorting and Searching, The Art of Computer Programming, vol. 3. Addison Wesley, Redwood City, CA, 1973.

    Google Scholar 

  11. Li X., Kim Y.J., Govindan R., and Hong W. Multi-dimensional range queries in sensor networks. In Proc. 1st Int. Conf. on Embedded Networked Sensor Systems, 2003, pp. 5–7.

    Google Scholar 

  12. Madden S.R., Franklin M.J., Hellerstein J.M., and Hong W. TinyDB: an acquisitional query processing system for sensor networks. ACM Trans. Database Syst., 30(1):122–173, 2005.

    Article  Google Scholar 

  13. Nath S., Gibbons P.B., Seshan S., and Anderson Z.R. Synopsis diffusion for robust aggregation in sensor networks. In Proc. 2nd Int. Conf. on Embedded Networked Sensor Systems, 2004, pp. 250–262.

    Google Scholar 

  14. Reiss F., Garofalakis M., and Hellerstein J.M. Compact histograms for hierarchical identifiers. In Proc. 32nd Int. Conf. on Very Large Data Bases, 2006, pp. 870–881.

    Google Scholar 

  15. Wang W., Yang J., and Muntz R. STING: a statistical information grid approach to spatial data mining. In Proc. 23rd Int. Conf. on Very Large Data Bases, 1997, pp. 186–195.

    Google Scholar 

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Tanin, E. (2009). Hierarchical Data Summarization. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_536

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