Action prediction and identification of tempral user behavior

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Tempral: Time property
Discriminative: Which can distinguish objects from others
Stationary: Static, won't change
Bid on: Deal, buy something
Novel: New and interesting
Correlated: Related

    The paper aimed to use a novel solution for predicting user behaviors based on their history actions, like URLS clicked, queries issued, web services used. The main problem for temporal user behavior analysing lies in 3 aspects:
    1) What's the represantation
    2) Behavior Diversity
    3) Lack of Supervised Knowledge
    
    The targeting system model:
    
     
    
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