This dissertation presents a novel data-driven approach to solve the problem of improving customer loyalty and customer retention. The data mining concepts of action rules and meta actions are used to extract actionable knowledge from customer sur...
This dissertation presents a novel data-driven approach to solve the problem of improving customer loyalty and customer retention. The data mining concepts of action rules and meta actions are used to extract actionable knowledge from customer sur...
The art market is a large and growing part of the global economy. However, uncertainty about prices, which can be problematic for many shareholders, can inhibit the growth of this market. This work discusses methods for the development of a knowle...
Online systems present users with a vast amount of information and product/service offerings. In order to deal with this type of information overload, many top online websites use recommender systems to provide users with a more personalized, and ...
As the field of recommender systems has grown, more and more attention has been focused on the need forsystems that provide and tailor recommendations to groups of users, as opposed to individuals. We have identified open issues in group-based rec...
As the field of recommender systems has grown, more and more attention has been focused on the need forsystems that provide and tailor recommendations to groups of users, as opposed to individuals. We have identified open issues in group-based rec...
Net Promoter System (NPS) is well known as an evaluation measure of the growth engine of big companies in the business area. The ultimate goal of my research is to build an action rules and meta-actions based recommender system for improving NPS s...
Net Promoter System (NPS) is well known as an evaluation measure of the growth engine of big companies in the business area. The ultimate goal of my research is to build an action rules and meta-actions based recommender system for improving NPS s...
