Personalising mobile advertising based on users’ installed apps

Mobile advertising is a billion pound industry that is rapidly expanding. The success of an advert is measured based on how users interact with it. In this paper we investigate whether the application of unsupervised learning and association rule mining could be used to enable personalised targeting of mobile adverts with the aim of increasing the interaction rate. Over May and June 2014 we recorded advert interactions such as tapping the advert or watching the whole advert video along with the set of apps a user has installed at the time of the interaction. Based on the apps that the users have installed we applied k-means clustering to profile the users into one of ten classes. Due to the large number of apps considered we implemented dimension reduction to reduced the app feature space by mapping the apps to their iTunes category and clustered users based on the percentage of their apps that correspond to each iTunes app category. The clustering was externally validated by investigating differences between the way the ten profiles interact with the various adverts genres (lifestyle, finance and entertainment adverts). In addition association rule mining was performed to find whether the time of the day that the advert is served and the number of apps a user has installed makes certain profiles more likely to interact with the advert genres. The results showed there were clear differences in the way the profiles interact with the different advert genres and the results of this paper suggest that mobile advert targeting would improve the frequency that users interact with an advert

Personalising mobile advertising based on users’ installed apps

Mobile advertising is a billion pound industry that is rapidly expanding. The success of an advert is measured based on how users interact with it. In this paper we investigate whether the application of unsupervised learning and association rule mining could be used to enable personalised targeting of mobile adverts with the aim of increasing the interaction rate. Over May and June 2014 we recorded advert interactions such as tapping the advert or watching the whole advert video along with the set of apps a user has installed at the time of the interaction. Based on the apps that the users have installed we applied k-means clustering to profile the users into one of ten classes. Due to the large number of apps considered we implemented dimension reduction to reduced the app feature space by mapping the apps to their iTunes category and clustered users based on the percentage of their apps that correspond to each iTunes app category. The clustering was externally validated by investigating differences between the way the ten profiles interact with the various adverts genres (lifestyle, finance and entertainment adverts). In addition association rule mining was performed to find whether the time of the day that the advert is served and the number of apps a user has installed makes certain profiles more likely to interact with the advert genres. The results showed there were clear differences in the way the profiles interact with the different advert genres and the results of this paper suggest that mobile advert targeting would improve the frequency that users interact with an advert

Personalised privacy in pervasive and ubiquitous systems

Our world is edging closer to the realisation of pervasive systems and their integration in our everyday life. While pervasive systems are capable of offering many benefits for everyone, the amount and quality of personal information that becomes available raise concerns about maintaining user privacy and create a real need to reform existing privacy practices and provide appropriate safeguards for the user of pervasive environments. This thesis presents the PERSOnalised Negotiation, Identity Selection and Management (PersoNISM) system; a comprehensive approach to privacy protection in pervasive environments using context aware dynamic personalisation and behaviour learning. The aim of the PersoNISM system is twofold: to provide the user with a comprehensive set of privacy protecting tools and to help them make the best use of these tools according to their privacy needs. The PersoNISM system allows users to: a) configure the terms and conditions of data disclosure through the process of privacy policy negotiation, which addresses the current “take it or leave it” approach; b) use multiple identities to interact with pervasive services to avoid the accumulation of vast amounts of personal information in a single user profile; and c) selectively disclose information based on the type of information, who requests it, under what context, for what purpose and how the information will be treated. The PersoNISM system learns user privacy preferences by monitoring the behaviour of the user and uses them to personalise and/or automate the decision making processes in order to unburden the user from manually controlling these complex mechanisms. The PersoNISM system has been designed, implemented, demonstrated and evaluated during three EU funded projects

A Categorical Clustering of Publishers for Mobile Performance Marketing

Mobile marketing is an expanding industry due to the growth of mobile devices (e.g., tablets, smartphones). In this paper, we explore a categorical approach to cluster publishers of a mobile performance market, in which payouts are only issued when there is a conversion (e.g., a sale). As a case study, we analyze recent and real-world data from a global mobile marketing company. Several experiments were held, considering a first internal evaluation stage, using training data, clustering quality metrics and computational effort. In the second stage, the best method, COBWEB algorithm, was analyzed using an external evaluation based on business metrics, computed over test data, and that allowed an identification of interesting clusters.This article is a result of the project NORTE-01-0247-FEDER- 017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT Funda ̧ca ̃o para a Ciˆencia e Tecnologia within the Project Scope: UID/CEC/00319/2013

Model-driven Personalisation of Human-Computer Interaction across Ubiquitous Computing Applications

Personalisation is essential to Ubiquitous Computing (Ubicomp), which focuses on a human-centred paradigm aiming to provide interaction with adaptive content, services, and interfaces towards each one of its users, according to the context of the applications’ scenarios. However, the provision of that appropriated personalised interaction is a true challenge due to different reasons, such as the user interests, heterogeneous environments and devices, dynamic user behaviour and data capture. This dissertation focuses on a model-driven personalisation solution that has the main goal of facili-tating the implementation of a personalised human-computer interaction across different Ubicomp scenarios and applications. The research reported here investigates how a generic and interoperable model for personalisation can be used, shared and processed by different applications, among diverse devices, and across different scenarios, studying how it can enrich human-computer interaction. The research started by the definition of a consistent user model with the integration of context to end in a pervasive model for the definition of personalisations across different applications. Besides the model proposal, the other key contributions within the solution are the modelling frame-work, which encapsulates the model and integrates the user profiling module, and a cloud-based platform to pervasively support developers in the implementation of personalisation across different applications and scenarios. This platform provides tools to put end users in control of their data and to support developers through web services based operations implemented on top of a personalisa-tion API, which can also be used independently of the platform for testing purposes, for instance. Several Ubicomp applications prototypes were designed and used to evaluate, at different phases, both the solution as a whole and each one of its components. Some were specially created with the goal of evaluating specific research questions of this work. Others were being developed with a pur-pose other than for personalisation evaluation, but they ended up as personalised prototypes to better address their initial goals. The process of applying the personalisation model to the design of the latter should also work as a proof of concept on the developer side. On the one hand, developers have been probed with the implementation of personalised applications using the proposed solution, or a part of it, to assess how it works and can help them. The usage of our solution by developers was also important to assess how the model and the platform respond to the developers’ needs. On the other hand, some prototypes that implement our model-driven per-sonalisation solution have been selected for end user evaluation. Usually, user testing was conducted at two different stages of the development, using: (1) a non-personalised version; (2) the final per-sonalised version. This procedure allowed us to assess if personalisation improved the human-com-puter interaction. The first stage was also important to know who were the end users and gather interaction data to come up with personalisation proposals for each prototype. Globally, the results of both developers and end users tests were very positive. Finally, this dissertation proposes further work, which is already ongoing, related to the study of a methodology to the implementation and evaluation of personalised applications, supported by the development of three mobile health applications for rehabilitation

THE CONSENT OF MAN: AN EXAMINATION OF PRIVACY AWARENESS, SURVEILLANCE, AND PRIVACY POLICY (MIS)USE

The problem of privacy is nuanced, pervasive, and requires an elevated approach. Given the lack of consistency with regard to privacy’s conceptualization and operationalization, research is needed that examines variables related to privacy to better understand how privacy operates in the present day. This dissertation aims to better understand nuances of privacy by gauging knowledge of online privacy, technological affordances related to privacy, and knowledge of surveillance. In this study, human subjects from a large southern University were presented with an opportunity to use a privacy-invasive smartphone application. After doing so, they viewed one of three privacy policies. Finally, they answered survey items measuring privacy awareness and surveillance awareness. It was found that there were no significant main effects between modality of privacy policy shown and awareness of privacy nor awareness of surveillance. However, significant individual differences were found between two types of privacy policies. It was also found that a significant and positive relationship existed between awareness of privacy, and awareness of surveillance. It was also found that a relationship existed between awareness of privacy and awareness of the communication affordances of visibility and encryption. The present study concludes with implications that benefit communication theory, social media research, and legal bodies who seek to address issues with present day privacy policies

Health and Artificial Intelligence in the context of COVID-19 and beyond

This article introduces the main relevant aspects of ehealth or “digital health.” In this regard, by way of an introduction, the concept of health is addressed. In the second section, the core of this article, different aspects regarding the relationship between health and technology (HealthTech) are highlighted. Next, the importance of technology in order to deliver a preventive and personalized medicine, tailor-made to each patient, is addressed. Then, in the fourth section, some discriminatory situations that may arise due to not being able to access technology are discussed. Finally, I make some remarks regarding the so-called “Internet of Bodies"

How and Why to Read and Create Children's Digital Books

How and Why to Read and Create Children's Digital Books outlines effective ways of using digital books in early years and primary classrooms, and specifies the educational potential of using digital books and apps in physical spaces and virtual communities. With a particular focus on apps and personalised reading, Natalia Kucirkova combines theory and practice to argue that personalised reading is only truly personalised when it is created or co-created by reading communities. Divided into two parts, Part I suggests criteria to evaluate the educational quality of digital books and practical strategies for their use in the classroom. Specific attention is paid to the ways in which digital books can support individual children’s strengths and difficulties, digital literacies, language and communication skills. Part II explores digital books created by children, their caregivers, teachers and librarians, and Kucirkova also offers insights into how smart toys, tangibles and augmented/virtual reality tools can enrich children’s reading for pleasure

How and Why to Read and Create Children's Digital Books

How and Why to Read and Create Children's Digital Books outlines effective ways of using digital books in early years and primary classrooms, and specifies the educational potential of using digital books and apps in physical spaces and virtual communities. With a particular focus on apps and personalised reading, Natalia Kucirkova combines theory and practice to argue that personalised reading is only truly personalised when it is created or co-created by reading communities. Divided into two parts, Part I suggests criteria to evaluate the educational quality of digital books and practical strategies for their use in the classroom. Specific attention is paid to the ways in which digital books can support individual children’s strengths and difficulties, digital literacies, language and communication skills. Part II explores digital books created by children, their caregivers, teachers and librarians, and Kucirkova also offers insights into how smart toys, tangibles and augmented/virtual reality tools can enrich children’s reading for pleasure