Online Models for Content Optimization

by Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, Nitin Motgi, Seung-Taek Park, Raghu Ramakrishnan, Scott Roy, Joe Zachariah

This is something very detailed for how Yahoo!'s today module is optimized for overall CTR. Internally the project was first named COKE but later rebranded as CORE (content optimization and relevence engine).

Here I only include some key points from the paper. Overall, the paper is written in a very succinct way and worth your time.

• mini batch learning in 5 minute segs;
• online models to track CTR including EMP, SS and OLR
• E&E setting with a random bucket

Let's take a look at the modelling part. Strangely still, I am very clear about the OLR part:

• it is a Bayesian version of logistic regression, Gaussian prior on parameters
• approximate inference with Laplace approximation scheme
• it may be simplified with uncorrelation assumption but the performance will suffer;

As for EMP and SS, SS is simply user-segmented EMP, i.e. building several EMP for each user segment. EMP looks like a Kalman filter (LDS) which I will take a detailed look soon.

Image Saliency: From Intrinsic to Extrinsic Context

by Meng Wang, Janusz Konrad, Prakash Ishwar and Kevin Jing, Henry Rowley

The method contains three steps:

• by kNN, the given image's saliency is computed from the images in the dictionary (global or patch by patch basis);
• a warping algorithm helps to align the kNN to the original image/patch
• the saliency is the reconstruction error

The idea is to find those part of the image that can't be explained by its neighbors (i.e. might be salient enough to catch your attention).

We may use an extra dictionary or we may simply split the image into patches.

Enhancing by Saliency-guided Decolorization

by Codruta Orniana Ancuti, Cosmin Ancuti and Phillipe Bekaert

This paper talks about a de-colorization method (maybe useful for de-saturating photos?). The basic idea is quite simple: the ultimate luminance is the original one multiplied by a coefficient that is defined by hue and saturation. There are certain tuning for the highlighted regions. I just got a simple experiment with OpenCV. But it doesn't work very well...