A Study on Data Association - Rules Mining of Content - Based Multimedia


The KIPS Transactions:PartD, Vol. 9, No. 1, pp. 57-64, Feb. 2002
10.3745/KIPSTD.2002.9.1.57,   PDF Download:

Abstract

Few studies have been systematically pursued on a multimedia data mining in despite of the overwhelming amounts of multimedia data by the development of computer capacity, storage technology and Internet. Based on the preliminary image processing and content-based image retrieval technology, this paper presents the methods for discovering association rules from recurrent items with spatial relationships in huge data repositories. Furthermore, multimedia mining algorithm is proposed to find implicit association rules among objects of which content-based descriptors such as color, texture, shape and etc. are recurrent and of which descriptors have spatial relationships. The algorithm with recurrent items in images shows high efficiency to find set of frequent items as compared to the Apriori algorithm. The multimedia association-rules algorithm is specially effective when the collection of images is homogeneous and it can be applied to many multimedia-related application fields.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
J. O. KIm and D. J. Hwang, "A Study on Data Association - Rules Mining of Content - Based Multimedia," The KIPS Transactions:PartD, vol. 9, no. 1, pp. 57-64, 2002. DOI: 10.3745/KIPSTD.2002.9.1.57.

[ACM Style]
Jin Ok KIm and Dae Joon Hwang. 2002. A Study on Data Association - Rules Mining of Content - Based Multimedia. The KIPS Transactions:PartD, 9, 1, (2002), 57-64. DOI: 10.3745/KIPSTD.2002.9.1.57.