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ARM On Multi-Media

ARM On Multi-Media. This project is on performing Association Rule Mining on Multimedia Data, particularly pictures and text. So, it essentially presents two challenges: ARM on Pictures ARM on Multiple tables. By Bhavika, Hau San, Juveria, Muhammad. Juveria Kanodia

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ARM On Multi-Media

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  1. ARM On Multi-Media This project is on performing Association Rule Mining on Multimedia Data, particularly pictures and text. So, it essentially presents two challenges: ARM on Pictures ARM on Multiple tables. By Bhavika, Hau San, Juveria, Muhammad.

  2. Juveria Kanodia • Each of us collected 200 annotated images. So we have a collection of 798 images and their text. • The features returned by Vishal for each image are imagename, R, G, B, Y, 0, 45, 90, 135, intensity. • Made a program to append a number to each feature so that it can be distinguished • Found a paper that discusses ARM on multi-relational data using Peano Trees. • The brief summary of what I found out:This paper is a good start, it suggests using constellation model for the job. It does some experiments to show that P-trees work best for joins and selection. • 6. Another Paper read on P-trees.

  3. Hau San Si Tou • Collected 200 pictures with picture descriptions • Wrote a program to handle the text input • Format: <pictureID> picture description • remove stop words, duplicate words • only unique keywords are left, act as itemsets • Tested with Christian Borgelt's Apriori implementation • different options available: -c, -s, -m, -n • used the keyword list from the picture description as an input file and generate association rules • Problem identified and solution • Problem: domain of the picture collection is too broad • a large number of different keywords • rules generated are of low support value • Solution: duplicate some of the picture descriptions to increase the support • Read some more papers on association rule mining

  4. Muhammad Data Collection Done ARM on Image data (Discretized) using Apriori Got many rules but have to make sense of these rules Papers on ARM: List available online http://www.cs.rit.edu/~maa2454/MRDM.htm Next Task: Implement WARMR - Automate storage of data as PROLOG Declarations Issues to be resolved: Access: WARMR vs. Decentralized Apriori vs. trees

  5. Bhavika • ARM on image data . • Collection of 200 images and description. • Application of fpgrowth on new feature data. • Understanding Peano-tree algorithm.

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