Email this article Smooth Non-negative Matrix Factorization framework for visually appealing storyboard
Abstract
We present a novel framework to consequently identify occasions from search log information and produce storyboards where the occasions are orchestrated sequentially. We picked picture look log as the asset for occasion mining, as search logs can straightforwardly mirror individuals' inclinations. To find occasions from log information, we present a Smooth Nonnegative Matrix Factorization structure (SNMF) which consolidates the data of question semantics, transient relationships, search logs and time congruity. Also, we consider the time factor a significant component since various occasions will create in various time inclinations. Also, to give a media-rich and outwardly engaging storyboard, every occasion is related with a lot of delegate photographs orchestrated along a course of events. These applicable photographs are naturally chosen from picture query items by investigating picture content features.
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