Added the capability of incremental SVD to python-recsys which is "Folding-in" new users (or items) to the SVD model so they can receive recommendations instantly without re-building the model from scratch each time new users come to the system.

[Ibrahim-AbouElseoud]

• Now supports incrementally adding new users or items instead of building the model from scratch for these new users or items via the folding-in technique which was mentioned in Sarwar et al.'s paper_ (Titled: Incremental Singular Value Decomposition Algorithms for Highly Scalable Recommender Systems), this latest commit is simply an implementation to it for python-recsys.

.. _paper: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.3.7894&rep=rep1&type=pdf

• A Demonstration video is available_ for this latest commit in form of a demo site built using the MEAN stack which uses the updated python-recsys as backend for the recommender which folds-in the website's user in to the SVD model and gets recommendations instantaneously instead of building the model from scratch.

.. _Demonstration video is available: https://youtu.be/tIvQxBfa2d4

• There is also an accompanying bachelor thesis paper_ (For those interested) which outlines the background, architecture and discusses the "Folding-in" approach.

.. _bachelor thesis paper: https://drive.google.com/file/d/0BylQe2cRVWE_RmZoUTJYSGZNaXM/view