This paper describes a novel approach to product recommendation that is based on
opinionated product descriptions that are automatically mined from user-generated product …

In the world of recommender systems, so-called content-based methods are an important
approach that rely on the availability of detailed product or item descriptions to drive the …

User-written product reviews contain rich information about user preferences for product
features and provide helpful explanations that are often used by shoppers to make their …

Increasingly large numbers of customers are choosing online shopping because of its
convenience, reliability, and cost. As the number of products being sold online increases, it …

Supplementing product information with user-generated content such as ratings and reviews
can help to convert browsers into buyers. As a result this type of content is now front and …

E-commerce recommender systems seek out matches between customers and items in
order to help customers discover more relevant and satisfying products and to increase the …

Many users of e-commerce portals commonly use customer reviews for making purchase
decisions. But a product may have tens or hundreds of diverse reviews leading to …

This paper describes a new method for providing recommendations tailored to a user's
preferences using text mining techniques and online technical specifications of products. We …

In this paper we build on recent work on case-based product recommendation focused on
generating rich product descriptions for use in a recommendation context by mining user …

With the growing popularity and acceptance of e-commerce platforms, users face an ever
increasing burden in actually choosing the right product from the plethora of online offers …