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Association Rule Mining on Multi-Media Data. Auto Annotation on Images Bhavika Patel Hau San Si Tou Juveria Kanodia Muhammad Ahmad. Auto Annotation on Images. This project is on performing Association Rule Mining on Multi-relational, Multimedia Data, particularly pictures and text.
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Association Rule Mining on Multi-Media Data Auto Annotation on Images Bhavika Patel Hau San Si Tou Juveria Kanodia Muhammad Ahmad
Auto Annotation on Images • This project is on performing Association Rule Mining on Multi-relational, Multimedia Data, particularly pictures and text. • Corpus: a group of 798 picturesof different kinds such as art, landscape … with descriptions • Generate association rules on image data (the RGBY values), and on text data separately. Propose an algorithm to link these two different domains together. • Goal: return words that will describe a given unknown picture
# of text association rules generated from different combination of min supp & conf
# of image association rules generated from different combination of min supp & conf
Single pass rebuild • Specify common key • Rebuild the tables based on the common key • Use Apriori • EXAMPLE: Table 1: purchase(customer,item,amount) item(customer,item_id) Table 2 purchase_total(customer,items) Query: Customers who buy a lot of stuff what do they usually but? purchase_total(X,items) return item(X,item_id)
Conclusion • So we have a partial solution multimedia ARM problem, however there many things that can be done further, to improve upon it. • Need to find a way to restrict the number of keywords that we get. • Need to find an easier method than the present lookup method, as too many files are involved. • Need for an efficient data structure to do the above point. • Alternative Schemes
The End Please visit our project’s website at http://www.cs.rit.edu/~p759-06c to find detailed information.