Algorithm-based decision support systems play an increasingly important role in decisions involving exploration tasks, such as product searches, portfolio choices, and human resource procurement. These tasks often involve a trade-off between exploration and exploitation, which can be highly...

The way each person dresses has been considered a cultural manifestation and a portrait of societies, where each one expresses their habits, customs and values. The improvement in living standards, especially in developed countries, accompanied by the emergence of Fast fashion, has led to an...

It has been conjectured that the peer-based recommendations associated with electronic commerce lead to a redistribution of demand from popular products or "blockbusters" to less popular or "niche" products, and that electronic markets will therefore be characterized by a "long tail" of demand...

In content- and knowledge-based recommender systems often a measure of (dis)similarity between products is used. Frequently, this measure is based on the attributes of the products. However, which attributes are important for the users of the system remains an important question to answer. In...

Recommender systems are becoming integral to how consumers discover media. The value that recommenders offer is personalization: in environments with many product choices, recommenders personalize the browsing and consumption experience to each userÕs taste. Popular applications include product...

Most recommender systems present recommended products in lists to the user. By doing so, much information is lost about the mutual similarity between recommended products. We propose to represent the mutual similarities of the recommended products in a two dimensional space, where similar...