There are many e-commerce applications on the web. A common shortcoming is the lack of customer service and marketing analysis tools in most ecommerce web sites. In order to overc...
Since the development of the comparably simple neighborhood-based methods in the 1990s, a plethora of techniques has been developed to improve various aspects of collaborative fil...
We propose a hybridization of collaborative filtering and content based recommendation system. Attributes used for content based recommendations are assigned weights depending on ...
This thesis investigates application of clustering to multi-criteria ratings as a method of improving the precision of top-N recommendations. With the advent of ecommerce sites th...
We propose a novel collaborative recommendation approach to take advantage of the information available in user-created lists. Our approach assumes associations among any two item...