Exploring uplift modelling in direct marketing

Purpose: This research examines the importance of an uplift marketing model compared to traditional response models, used in direct marketing. Research Methodology: A multi-method research approach was used which included a survey using an electronic questionnaire and a semi-structured interview. Results: The research findings reveal that the value of employing uplift models in direct marketing. is that it factors change in behaviour from the action, which traditional response models do not. Limitation: The study was conducted in a single institution and focused only on scustomers with banking needs. Contribution: By employing an uplift model in direct marketing it is possible to increase marketing return-on-investment and positively impact brand loyalty and brand perception. Thus, marketers need to be cognizant of these findings and strategize accordingly. Keywords: Direct marketing, Customer management, Marketing model, Marketing communicatio

Integrating expert knowledge with data in Bayesian networks: Preserving data-driven expectations when the expert variables remain unobserved

When developing a causal probabilistic model, i.e. a Bayesian network (BN), it is common to incorporate expert knowledge of factors that are important for decision analysis but where historical data are unavailable or difficult to obtain. This paper focuses on the problem whereby the distribution of some continuous variable in a BN is known from data, but where we wish to explicitly model the impact of some additional expert variable (for which there is expert judgment but no data). Because the statistical outcomes are already influenced by the causes an expert might identify as variables missing from the dataset, the incentive here is to add the expert factor to the model in such a way that the distribution of the data variable is preserved when the expert factor remains unobserved. We provide a method for eliciting expert judgment that ensures the expected values of a data variable are preserved under all the known conditions. We show that it is generally neither possible, nor realistic, to preserve the variance of the data variable, but we provide a method towards determining the accuracy of expertise in terms of the extent to which the variability of the revised empirical distribution is minimised. We also describe how to incorporate the assessment of extremely rare or previously unobserved events

Bayesian δίκτυα και εύρεση δομής με ακριβή αλγόριθμο

Η εύρεση δομής σε Bayesian δίκτυα έχει απασχολήσει πολλούς ερευνητές την τελευταία δεκαετία. Οι εφαρμογές τους ποικίλλουν, από τον αθλητισμό, την ψυχαγωγία μέχρι και την ιατρική. Ο σκοπός της εργασίας αυτής είναι να παρουσιάσει τα βασικά χαρακτηριστικά των Bayesian δικτύων, να αναλύσει τη δομή τους και να επικεντρωθεί στο πρόβλημα της εύρεσης αυτής της δομής. Συγκρίνονται διαφορετικές μέθοδοι για την επίλυση του προβλήματος αυτού και υλοποιείται ένας ακριβής αλγόριθμος για την εύρεση της δομής τέτοιων δικτύων μέσα από δεδομένα που παρέχονται. Στόχος της εργασίας είναι επίσης η ενσωμάτωση αυτού του αλγορίθμου στο πρόγραμμα ΑΙΤΙΟΝ. Τέλος, εκτελούνται πειραματικές μελέτες με σκοπό την εξακρίβωση της αποδοτικότητας του αλγορίθμου αυτού και παρουσιάζονται τα αποτελέσματα τους.Structure discovery has been the main focus on multiple research papers during the last decade. It can be applied in many fields including sports, entertainment and even medical science. The purpose of this thesis is to present the basic characteristics of Bayesian networks, to analyse their structure and to emphasise on the problem of discovering this structure. Various different solutions are compared and an exact algorithm for Bayesian structure discovery through data is implemented. In addition to this, a focal point is the incorporation of this algorithm in the AITION platform. Finally, experiments are conducted to prove the efficiency of the algorithm and their results presented thoroughly.

Políticas de Copyright de Publicações Científicas em Repositórios Institucionais: O Caso do INESC TEC

A progressiva transformação das práticas científicas, impulsionada pelo desenvolvimento das novas Tecnologias de Informação e Comunicação (TIC), têm possibilitado aumentar o acesso à informação, caminhando gradualmente para uma abertura do ciclo de pesquisa. Isto permitirá resolver a longo prazo uma adversidade que se tem colocado aos investigadores, que passa pela existência de barreiras que limitam as condições de acesso, sejam estas geográficas ou financeiras. Apesar da produção científica ser dominada, maioritariamente, por grandes editoras comerciais, estando sujeita às regras por estas impostas, o Movimento do Acesso Aberto cuja primeira declaração pública, a Declaração de Budapeste (BOAI), é de 2002, vem propor alterações significativas que beneficiam os autores e os leitores. Este Movimento vem a ganhar importância em Portugal desde 2003, com a constituição do primeiro repositório institucional a nível nacional. Os repositórios institucionais surgiram como uma ferramenta de divulgação da produção científica de uma instituição, com o intuito de permitir abrir aos resultados da investigação, quer antes da publicação e do próprio processo de arbitragem (preprint), quer depois (postprint), e, consequentemente, aumentar a visibilidade do trabalho desenvolvido por um investigador e a respetiva instituição. O estudo apresentado, que passou por uma análise das políticas de copyright das publicações científicas mais relevantes do INESC TEC, permitiu não só perceber que as editoras adotam cada vez mais políticas que possibilitam o auto-arquivo das publicações em repositórios institucionais, como também que existe todo um trabalho de sensibilização a percorrer, não só para os investigadores, como para a instituição e toda a sociedade. A produção de um conjunto de recomendações, que passam pela implementação de uma política institucional que incentive o auto-arquivo das publicações desenvolvidas no âmbito institucional no repositório, serve como mote para uma maior valorização da produção científica do INESC TEC.The progressive transformation of scientific practices, driven by the development of new Information and Communication Technologies (ICT), which made it possible to increase access to information, gradually moving towards an opening of the research cycle. This opening makes it possible to resolve, in the long term, the adversity that has been placed on researchers, which involves the existence of barriers that limit access conditions, whether geographical or financial. Although large commercial publishers predominantly dominate scientific production and subject it to the rules imposed by them, the Open Access movement whose first public declaration, the Budapest Declaration (BOAI), was in 2002, proposes significant changes that benefit the authors and the readers. This Movement has gained importance in Portugal since 2003, with the constitution of the first institutional repository at the national level. Institutional repositories have emerged as a tool for disseminating the scientific production of an institution to open the results of the research, both before publication and the preprint process and postprint, increase the visibility of work done by an investigator and his or her institution. The present study, which underwent an analysis of the copyright policies of INESC TEC most relevant scientific publications, allowed not only to realize that publishers are increasingly adopting policies that make it possible to self-archive publications in institutional repositories, all the work of raising awareness, not only for researchers but also for the institution and the whole society. The production of a set of recommendations, which go through the implementation of an institutional policy that encourages the self-archiving of the publications developed in the institutional scope in the repository, serves as a motto for a greater appreciation of the scientific production of INESC TEC