A Text-Based and Self-Adapting Product Recommendation Engine

Content-based recommendation engines are typically done in two steps. In the first, a user-preference model is constructed using a set of predefined features. (For example, in the context of retail, we may have features like Price Sensitivity, Promotion Sensitivity, Coupon Redeemer, Calorie Counter, Working Mums, etc.) In the second step, products are mapped, either directly … More A Text-Based and Self-Adapting Product Recommendation Engine

Online Support Vector Machines

I have been studying and experimenting with online learning algorithms for support vector machines (SVMs) for a while now, primarily with the intention of understanding how they can be used to learn SVM models on large multi-terabyte datasets. The following technical report describes the NORMA and PEGASOS family of algorithms and give some observations and relevant … More Online Support Vector Machines