We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Taxonomy based Data Marts

by Asiya Abdus Salam Qureshi, Syed Muhammad Khalid Jamal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 60 - Number 13
Year of Publication: 2012
Authors: Asiya Abdus Salam Qureshi, Syed Muhammad Khalid Jamal
10.5120/9750-3582

Asiya Abdus Salam Qureshi, Syed Muhammad Khalid Jamal . Taxonomy based Data Marts. International Journal of Computer Applications. 60, 13 ( December 2012), 6-12. DOI=10.5120/9750-3582

@article{ 10.5120/9750-3582,
author = { Asiya Abdus Salam Qureshi, Syed Muhammad Khalid Jamal },
title = { Taxonomy based Data Marts },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 60 },
number = { 13 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 6-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume60/number13/9750-3582/ },
doi = { 10.5120/9750-3582 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:06:27.401794+05:30
%A Asiya Abdus Salam Qureshi
%A Syed Muhammad Khalid Jamal
%T Taxonomy based Data Marts
%J International Journal of Computer Applications
%@ 0975-8887
%V 60
%N 13
%P 6-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aim of this paper is to depict new approach called taxonomy based data marts which add a new layer for the categorization of the queries using data warehouse which is the database that contains data relevant to an organization information and respond quickly to multi dimensional analytical queries. The new algorithm is introduced here for more precise results and time saving consumption using data marts which collects data for specific set of users or knowledge workers. Data warehouses often adopt a three-tier architecture. The bottom tier is a warehouse database server, which is typically a relational database system. The middle tier is an OLAP server, and the top tier is a client that contains query and reporting tools. Another new layer is added for faster results. This is done with the help of query classification technique.

References
  1. AsiyaAbdusSalam Qureshi and Syed Muhammad Khalid jamal. 2012. Web supported query taxonomy classifier. In International Journal of Computer Application. , August 2012.
  2. S. M. Khalid Jamal, Naz. A. , "Dual Encrypted Global Metadata:an approach to secure metadata", Journal of Computer Science and Engineering, volume 14, issue 2, august 2012
  3. Christian Platzer, Clemens Kolbitsch and Manuel Egele. 2011. Removing web spam links from search engine results. In Journal in Computer Virology, Volume 7 Issue 1, February 2011, Pages 51-62, Springer-Verlag New York, Inc. Secaucus, NJ, USA.
  4. Alessandro marchetto, filipporicca and paolotonella. 2009. An empirical validation of a web fault taxonomy and its usage for web testing. In journal of web engineering, volume 8 issue 4, december 2009, pages 316-345, rinton press, incorporated.
  5. FabrizioSilvestri. 2010. Mining Query Logs: Turning Search Usage Data into Knowledge. In Journal of Foundations and Trends in Information Retrieval, Volume 4 Issue 1—2, January 2010 , Pages 1-174, Hanover, MA, USA.
  6. Jihie Kim, Peter Will, S. Ri Ling and Bob Neches. 2003. Knowledge-rich catalog services for engineering design. In Journal of Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Volume 17 Issue 4, September 2003, Pages 349 – 366, Cambridge University Press New York, NY, USA.
  7. Ying Li, Zijian Zhen and Honghua Dai. 2005. KDD CUP-2005 Report: Facing a Great Challenge. In SIGKDD Explorations Volume 7.
  8. UtkasrshSrivastava, KameshMunagala, Jennifer Widom and Rajeev Motwani. 2006. Query Optimization over Web Services. In VLDB'06 September 12-15, 2006, Seol, Korea, ACM.
  9. Pu-Jeng Cheng, Ching-Hsiang Tsai and Chen-Ming Hung. 2006. Query Taxonomy Generation for Web Search. In CIKM'06, November 5-11, 2006 Arlington, Virginia, USA, ACM.
  10. Joseph M. Hellerstein, Jeffrey F. Naughton. 1996 Query Execution Techniques for Caching Expensive Methods. In SIGMOD'96 6/96 Montreal, Canada, ACM.
  11. EvgeniyGabrilovich, Andrei broder, Marcus Fontoura, Amruta Joshi and VanjaJasifovski. 2007. Classifying Search Queries Using the Web as a Source of Knowledge. In ACM international Conference on Research and Development in Information Retrieval (SIGIR) Amsterdam, Netherlands.
  12. S. Chaudhuri,U. Dayal and T. Yan. 1995. Join queries with external text sources: Execution and optimization techbiques. In Proc. of the ACM SIGMOD Intl Conference on Management of Data,San Jose, California.
  13. Nikos Kirtsis and Sofia Stamou. 2011. Query Reformulation for Task Oriented web searches. In Proc. of IEEE/WIC/ACM Intl conference on Web Intelligence and Intelligent Agent Technology.
  14. Shuai Ding, Josh Attenberg, Ricardo Baeza and TorstenSuel. 2011. Batch Query Processing for web search engines. In proc. of the fourth ACM intl conference on web search and data mining
  15. Yuchen Liu, Xiaochuan Ni, Jian Tao sun and Zheng Chen. 2011. Unsupervised transactional query classification based on webpage form understanding. In proc. of 20th ACM intl conference on Information and knowledge management.
  16. Xianghua Fu, Dongjian Chen, XuepingGuo and Chao Wang. 2011. Query classification based on index association rule expansion. In proc of intl conference on web information systems and mining volume part 2.
  17. Edwards, J. , McCurley, K. S. , and Tomlin, J. A. 2001. An adaptive model for optimizing performance of an incremental web crawler. In Proceedings of the Tenth Conference on World Wide Web (Hong Kong: Elsevier Science
  18. S. Dessloch and N. Mattos. 1997. Integrating SQL databases with content specific search engines. In proc. of 23rdintl conference on very large database, Greece.
  19. D. Florescu, A. Levy, I. Manolescu and D. Suciu. 1999. Query optimization in the presence of limited access patterns. In proc. of ACM SIGMOD Intl conference on Management of Data, Pennsylvania.
  20. L. Gravano, V. Hatzivassiloglou and R. Lichtenstein. 2003. Categorizing web queries according to geographical locality. In CIKM 03: Proc of 12thintl conference on Information and knowledge management.
  21. S. M. Beitzel, E. C. Jensen,O. Frieder, D. Grossman, D. D. Lewis, A. Chowdhury and A. Kolcz. 2005. Automatic web query classification using labeled and unlabeled training data. In SIGIR 05: Proc of 28th annual international ACM SIGIR conference on Research and development in information retrieval.
Index Terms

Computer Science
Information Sciences

Keywords

Query Classification Bridging Classifier Category Selection Data Marts Taxonomy based data marts Data warehouse OLAP server