A case study of exploiting data mining techniques for an industrial recommender system

This is an electronic version of the paper presented at the 1st International Workshop on Recommender-based Industrial Applications, held in New York on 2009We describe a case study of the exploitation of Data Mining techniques for creating an industrial recommender system. The aim of this system is to recommend items of a fashion retail store chain in Spain, producing leaflets for loyal customers announcing new products that they are likely to want to purchase. Motivated by the fact of having little information about the customers, we propose to relate demographic attributes of the users with content attributes of the items. We hypothesise that the description of users and items in a common content-based feature space facilitates the identification of those products that should be recommended to a particular customer. We present a recommendation framework that builds Decision Trees for the available demographic attributes. Instead of using these trees for classification, we use them to extract those content-based item attributes that are most widespread among the purchases of users who share the demographic attribute values of the active user. We test our recommendation framework on a dataset with oneyear purchase transaction history. Preliminary evaluations show that better item recommendations are obtained when using demographic attributes in a combined way rather than using them independently.This research was supported by the European Commission under contracts FP6-027122-SALERO, FP6-033715-MIAUCE and FP6-045032 SEMEDIA. The expressed content is the view of the authors but not necessarily the view of SALERO, MIAUCE and SEMEDIA projects as a whole

The influence of national culture on the attitude towards mobile recommender systems

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This study aimed to identify factors that influence user attitudes towards mobile recommender systems and to examine how these factors interact with cultural values to affect attitudes towards this technology. Based on the theory of reasoned action, belief factors for mobile recommender systems are identified in three dimensions: functional, contextual, and social. Hypotheses explaining different impacts of cultural values on the factors affecting attitudes were also proposed. The research model was tested based on data collected in China, South Korea, and the United Kingdom. Findings indicate that functional and social factors have significant impacts on user attitudes towards mobile recommender systems. The relationships between belief factors and attitudes are moderated by two cultural values: collectivism and uncertainty avoidance. The theoretical and practical implications of applying theory of reasoned action and innovation diffusion theory to explain the adoption of new technologies in societies with different cultures are also discussed.National Research Foundation of Korea Grant funded by the Korean governmen

Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal

The purpose of this paper is to understand, with an emphasis on the psychological perspective of the research problem, the consumer's adoption and use of a certain web site recommendation system as well as the main psychological outcomes involved. The approach takes the form of theoretical modelling. Findings: A conceptual model is proposed and discussed. A total of 20 research propositions are theoretically analyzed and justified. Research limitations/implications: The theoretical discussion developed here is not empirically validated. This represents an opportunity for future research. Practical implications: The ideas extracted from the discussion of the conceptual model should be a help for recommendation systems designers and web site managers, so that they may be more aware, when working with such systems, of the psychological process consumers undergo when interacting with them. In this regard, numerous practical reflections and suggestions are presented