Personalization

Personalization (broadly known as customization) consists of tailoring a service or a product to accommodate specific individuals, sometimes tied to groups or segments of individuals. A wide variety of organizations use personalization to improve customer satisfaction, digital sales conversion, marketing results, branding, and improved website metrics as well as for advertising. Personalization is a key element in social media and recommender systems. Personalization is affecting every sector of society—work, leisure, and citizenship. History of Personalization The idea of personalization is rooted in ancient rhetoric as part of the practice of an agent or communicator being responsive to the needs of the audience. When industrialization led to the rise of mass communication, the practice of message personalization diminished for a time. But the significant increase in the number of mass media outlets that use advertising as a primary revenue stream, and as they sought to a

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Privacy-preserving and Personalized Federated Machine Learning for Medical Data

Felix Hans Michel Grimberg

The federated learning setting is prone to suffering from non-identically distributed data across participating agents. This gives rise to the task of model personalization, where agents collaborate to train several different machine learning models instead of training only one global model. The aim of model personalization is to minimize the sum of the generalization error incurred from training on small data sets, and the transfer error incurred from applying a globally-trained model to a specific local distribution. In this report, two novel approaches to personalized cross-silo federated learning are introduced and discussed from a theoretical perspective: the adapted Ndoye factor, and the Weight Erosion aggregation scheme. The latter is implemented and compared to two baseline aggregation schemes in two case studies: training a diagnostic model on real-world medical data, and predicting the survival of passengers on the publicly available Titanic data set. The models trained using the Weight Erosion aggregation scheme are compared to those trained using the baseline aggregation schemes, both in terms of their classification accuracy on the local test set and in terms of the learned parameters. We demonstrate that the novel Weight Erosion scheme can outperform both baseline aggregation schemes for some specific tasks.

2020

Identifying a Motivational Profile for Older Adults Towards Increased Physical Activity

Yuan Lu, Pearl Pu Faltings

Personalizing behavior change (BC) strategies to motivate increased physical activity is especially important for the diverse older adult population. However, there is a lack of knowledge about how to profile older users to most effectively personalize BC solutions. Self-awareness and social awareness are BC strategies commonly used in commercially available applications to promote physical activities. Through a randomized controlled trial (N = 53), we studied the effect of some personal factors on the physical activity of older adults under these two strategies. For this purpose, each BC strategy was implemented in a mobile application. Based on the statistical analysis of the measured step data and the collected questionnaire data, we identified a list of personal factors to personalize each BC strategy towards improved physical activity. Hereby we suggest how to create effective motivational profiles and provide design recommendations to personalize these BC strategies toward increased physical activity for older users.

2021

EHR: a Sensing Technology Readiness Model for Lifestyle Changes

Yu Chen, Danni Le, Pearl Pu Faltings, Zerrin Yumak

Interest in developing user-centered sensing technologies for personalized behavior change has gained significant momentum. However, very little research work has been done to understand issues relative to user readiness and adoption of the sensing technologies to change their behaviors, especially the motivations as well as the concerns and impediments for adoption. We have developed a model called EHR (e-health readiness), to understand and explain the relationship between user habits, perceived healthiness and beliefs towards sensing technologies, and how these factors influence user readiness to use sensing technologies to manage their wellness. We then validate the model using psychometric methods by a large-scale user study (N = 541). Results show overall readiness to sensing technologies is positively influenced by readiness to monitor health conditions, share data within social networks, and receive recommendations. Additionally, readiness is significantly impacted by perceptions of healthiness, technology satisfaction and usefulness of such technology. Finally, we summarize user motivations and concerns for pervasive sensing tools through qualitative analysis on their comments. We present this model and the results of this survey to shed light on designing future sensing technologies for behavior change.

Springer2017

AR-219: Advanced CAO and Integrated Modeling DIM

1ère année: bases nécessaires à la représentation informatique 2D (3D). Passage d'un à plusieurs logiciels: compétence de choisir les outils adéquats en 2D et en 3D. Mise en relation des outils de CAO et DIM: regard critique et aptitude à choisir les méthodes nécessaires au résultat recherché.

MGT-426: Logistics and demand analysis

Ce cours a pour objectif de présenter la fonction logistique de l'entreprise dans le cadre d'une approche globale, de la logistique au supply chain management, en insistant sur l'importance de la demande "client" tirant tous processus de la chaîne d'ajout de valeur du produit ou du service

CS-421: Machine learning for behavioral data

Computer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will cover the core methods of user modeling and personalization, with a focus on educational data.

Targeted advertising

Targeted advertising is a form of advertising, including online advertising, that is directed towards an audience with certain traits, based on the product or person the advertiser is promoting. Thes

Mass customization

In marketing, manufacturing, call centre operations, and management, mass customization makes use of flexible computer-aided systems to produce custom output. Such systems combine the low unit costs

Recommender system

A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that provide suggestions for