International Journal of Information Technology and Computer Science(IJITCS)
ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)
Published By: MECS Press
IJITCS Vol.9, No.6, Jun. 2017
Application of Materialized View in Incremental Data Mining Operation
Full Text (PDF, 405KB), PP.43-49
Materialized view is a database object used to store the results of a query set. It is used to avoid the costly processing time that is required to execute complex queries involving aggregation and join operations. Materialized view may be associated with the operations of a data warehouse. Data mining is a technique to extract knowledge from a data warehouse and the incremental data mining is another process that periodically updates the knowledge that has been already identified by a data mining process. This happens when a new set of data gets added with the existing set. This paper proposes a method to apply the materialized view in incremental data mining.
Cite This Paper
Debabrata Datta, Kashi Nath Dey,"Application of Materialized View in Incremental Data Mining Operation", International Journal of Information Technology and Computer Science(IJITCS), Vol.9, No.6, pp.43-49, 2017. DOI: 10.5815/ijitcs.2017.06.06
Debabrata Datta and Kashi Nath Dey, "A Soft Computing Approach of Materialized View Creation", Proceedings of the 3rd International Conference on Business & Information Management, National Institute of Technology, Durgapur, India, January, 2016.
T. Morzy, M. Wojciechowski and M. Zakrzewicz, “Materialized Data Mining Views”, Proceedings of the Fourth European Conference on Principles of Data Mining and Knowledge Discovery, 2000, pp. 65 – 74.
Agarwal R. and Srikant, R., “Fast Algorithms for Mining Association Rules”, Proceedings of the 20th International Conference on Very Large Data Bases, 1994, pp. 487 – 499.
R. Agrawal, T. Imielinski and A. Swami, “Mining Association Rules Between Sets of Items in Large Databases”. Proceedings of the ACM SIGMOD Conference on Management of Data, 1993, pp. 207 – 216.
D. W.-L. Cheung, J. Han, V. Ng, and C. Y. Wong, “Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique”, Proceedings of the 12th International Conference on Data Engineering, 1996, pp. 106 – 114.
Thomas S., Bodagala S., Alsabti K. and Ranka S, “An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases”, Proceedings of the International Conference on Knowledge Discovery in Databases, 1997, pp. 263 – 266.
Parthasarathy, M., J. Zaki, M. Ogihara and S. Dwarkadas, “Incremental and Interactive Sequence Mining”, Proceedings of the ACM CIKM Conference, 1999, pp. 251 – 258.
Czejdo, Bogdan, Morzy, Mikolaj, Wojciechowski, Marek and Zakrzewicz, Maciej, “Materilaized View in Data Mining”, Proceedings of the 13th International Workshop on Database and Expert Systems Applications, 2002, pp. 827 – 831.
Debabrata Datta and Kashi Nath Dey, "Materialized View Generation using Apriori Algorithm", International Journal of Database Management Systems, Vol - 7, No. – 6 ISSN: 0975-5705, 2015, pp. 17 – 27.
Morzy, MikoÃlaj, Morzy, Tadeusz and Kr´olikowski, Zbyszko, “Incremental Association Rule Mining Using Materialized Data Mining Views”, Proceedings of the International Conference on Advances of Information Systems, 2004, pp. 77 – 87.
Baralis E., Paraboschi S. and Teniente E, “Materialized view selection in a multidimensional database”, Proceeding of the 23rd International Conference on Very Large Data Bases, 1997, pp. 156 – 165.
Chaudhuri, S. & Dayal, U., “An Overview of Data Warehousing and OLAP Technology”. In ACM Sigmod Record, Volume 26, Issue 1, 1997, pp. 65 – 74.
Wojciechowski M. and Zakrzewicz M., “Itemset Materializing for Fast Mining of Association Rules”, Proceeding of the 2nd Conference on Advances in Databases and Information Systems, 1998.
Imielinski T. and Mannila H., ”A Database Perspective on Knowledge Discovery”, Communications of the ACM, Vol. 39, No. 11, 1996, pp. 58 – 64.
P.P. Karde and V.M.Thakare, “Selection & Maintenance of Materialized View and It’s Application for Fast Query Processing: A Survey”, International Journal of Computer Science & Engineering Survey, Volume 1, Number 2, 2010, pp. 16 – 29.
T. Nalini, A. Kumaravel and K. Rangarajan, “A comparative study analysis of materialized view for selection cost”, International Journal of Computer Science & Engineering Survey, Volume 3, Number 1, 2012, pp. 13 – 22.