Using Machine Learning to Improve Personalised Prediction: A Data-Driven Approach to Segment and Stratify Populations for Healthcare

Population Health Management typically relies on subjective decisions to segment and stratify populations. This study combines unsupervised clustering for segmentation and supervised classification, personalised to clusters, for stratification. An increase in cluster homogeneity, sensitivity and positive predictive value was observed compared to an unlinked approach. This analysis demonstrates the potential for a cluster-then-predict methodology to improve and personalise decisions in healthcare systems

PERSONALISING INFORMATION SECURITY EDUCATION

Whilst technological solutions go a long way in providing protection for users online, it has been long understood that the individual also plays a pivotal role. Even with the best of protection, an ill-informed person can effectively remove any protection the control might provide. Information security awareness is therefore imperative to ensure a population is well educated with respect to the threats that exist to one’s electronic information, and how to better protect oneself. Current information security awareness strategies are arguably lacking in their ability to provide a robust and personalised approach to educating users, opting for a blanket, one-size-fits-all solution. This research focuses upon achieving a better understanding of the information security awareness domain; appreciating the requirements such a system would need; and importantly, drawing upon established learning paradigms in seeking to design an effective personalised information security education. A survey was undertaken to better understand how people currently learn about information security. It focussed primarily upon employees of organisations, but also examined the relationship between work and home environments and security practice. The survey also focussed upon understanding how people learn and their preferences for styles of learning. The results established that some good work was being undertaken by organisations in terms of security awareness, and that respondents benefited from such training – both in their workplace and also at home – with a positive relationship between learning at the workplace and practise at home. The survey highlighted one key aspect for both the training provided and the respondents’ preference for learning styles. It varies. It is also clear, that it was difficult to establish the effectiveness of such training and the impact upon practice. The research, after establishing experimentally that personalised learning was a viable approach, proceeded to develop a model for information security awareness that utilised the already successful field of pedagogy and individualised learning. The resulting novel framework “Personalising Information Security Education (PISE)” is proposed. The framework is a holistic approach to solving the problem of information security awareness that can be applied both in the workplace environment and as a tool for the general public. It does not focus upon what is taught, but rather, puts into place the processes to enable an individual to develop their own information security personalised learning plan and to measure their progress through the learning experience.Ministry Of Higher Education Malaysi

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

e-Consumer Behaviour

Purpose – The primary purpose of this article is to bring together apparently disparate and yet interconnected strands of research and present an integrated model of e-consumer behaviour. It has a secondary objective of stimulating more research in areas identified as still being underexplored. Design/methodology/approach – The paper is discursive, based on analysis and synthesis of econsumer literature. Findings – Despite a broad spectrum of disciplines that investigate e-consumer behaviour and despite this special issue in the area of marketing, there are still areas open for research into econsumer behaviour in marketing, for example the role of image, trust and e-interactivity. The paper develops a model to explain e-consumer behaviour. Research limitations/implications – As a conceptual paper, this study is limited to literature and prior empirical research. It offers the benefit of new research directions for e-retailers in understanding and satisfying e-consumers. The paper provides researchers with a proposed integrated model of e-consumer behaviour. Originality/value – The value of the paper lies in linking a significant body of literature within a unifying theoretical framework and the identification of under-researched areas of e-consumer behaviour in a marketing context

Service design for Rural Heritage Tourism

‘i am not a tourist’. – Why collaborative service design may be the key to developing sustainable cultural & rural visitor economies, with the help of ICT, social media and crowdsourcing Abstract: This paper will outline how the practice of Service Design can facilitate the creation of sustainable cultural and rural visitor economies, with the help of ICT, social media and crowd sourcing. This paper is not written to be ‘value-neutral’, but is motivated by the author’s belief that academic activism in tourism ‘must be with the communities and not for them: solidarity is the basis where our common concern is mutual empowerment, self-determination and emancipation.’ (Hales et al.,2013, p17) The aim of the paper is to identify how Service Design and its processes, such as co-creation, have the potential to develop cultural and rural tourism economies, which are community centric and allow the often-narrow role of the tourist to be humanised and democratised. Service Design will be discussed on the on the basis that ‘Design has shown itself to be an efficient way of improving a business’s profitability at a practical level, but when we recognize its capacity to transform environments and people’s lives, it also becomes a catalyst for social change.’ (Viladas 2011, p26) The paper will touch on the need for a democratically supported strategic framework, which ‘incorporates a broader set of values beyond economic growth’ (Hales et al., 2013, p12), and that design thinking has the ability to effect economic and cultural sustainability through co-creation and technology. Service Design thinking can be help define values and identities, that further the concept of tourism in a societal and economic context, by taking advantage of opportunities created in the digital realm by crowdsourcing and social media. The knowledge base of the author’s professional background is design and advertising, and the paper will aim to make sense of this knowledge in relation to sustainable tourism. In the latter part it will focus on the island of Crete to discuss how some of the Service Design and Advertising principles may be applied in practice and why a holistic service design strategy may be particularly suitable for community centered cultural and rural tourism on Crete

Online learning of personalised human activity recognition models from user-provided annotations

PhD ThesisIn Human Activity Recognition (HAR), supervised and semi-supervised training are important tools for devising parametric activity models. For the best modelling performance, large amounts of annotated personalised sample data are typically required. Annotating often represents the bottleneck in the overall modelling process as it usually involves retrospective analysis of experimental ground truth, like video footage. These approaches typically neglect that prospective users of HAR systems are themselves key sources of ground truth for their own activities. This research therefore involves the users of HAR monitors in the annotation process. The process relies solely on users' short term memory and engages with them to parsimoniously provide annotations for their own activities as they unfold. E ects of user input are optimised by using Online Active Learning (OAL) to identify the most critical annotations which are expected to lead to highly optimal HAR model performance gains. Personalised HAR models are trained from user-provided annotations as part of the evaluation, focusing mainly on objective model accuracy. The OAL approach is contrasted with Random Selection (RS) { a naive method which makes uninformed annotation requests. A range of simulation-based annotation scenarios demonstrate that using OAL brings bene ts in terms of HAR model performance over RS. Additionally, a mobile application is implemented and deployed in a naturalistic context to collect annotations from a panel of human participants. The deployment is proof that the method can truly run in online mode and it also shows that considerable HAR model performance gains can be registered even under realistic conditions. The ndings from this research point to the conclusion that online learning from userprovided annotations is a valid solution to the problem of constructing personalised HAR models

The Role of Self-congruity in Consumer Preferences: Perspectives from Transaction Records

Personalised marketing is more persuasive than traditional techniques aimed at the masses, however marketers do not always have access to consumers’ private attributes in order to apply these insights. The effect of personalisation is based on an established theory in consumer psychology – self-congruity theory – which posits that individuals prefer products, brands and advertisements that embody characteristics that match with their self-concepts. Self-congruence not only enhances marketing effectiveness, it can also be used to improve consumer well-being. While it has been established that consumers who spend in a way that is more congruent with their personality are happier, clarifications around the types of individuals who are more or less likely to engage in self-congruent spending, as well as the moderating effects on the benefit in happiness from such consumption could inform policy for improving happiness at a collective level. This thesis contributes to a growing body of research which attempts to understand how consumption patterns are related to consumers’ characteristics, its applications in advertising, as well as consumer well-being. By using a dataset containing more than 1 million transactions recorded over a period of 12-months, the thesis demonstrates the value of the digital footprint in the form of bank transactions for enriching our understanding of key questions in consumer research, underpinned by the theory of self-congruity. This thesis combines methods from computational social science with personality psychology to test research questions on consumer preferences. Two components of the thesis focused on the predictive utility of transaction records in inferring consumer attributes with which to personalise advertising, as well as the use of transaction records in examining self-congruence in overall consumption patterns and its relationship with happiness. Through five empirical studies, this work suggests that consumer attributes such as age and financial distress can be reliably inferred from consumption patterns reflected in transaction records (Chapter 3 and 5). The inferred age can be used to personalise advertisements in order to increase their appeal (Chapter 4). Using an objective measure of self-congruence in overall consumption pattern computed from transaction records and panel ratings, the thesis shows that individuals differ in their tendency to spend in a way that is congruent with their personality based on their levels of materialism and financial distress (Chapter 6). As the most important predictor of self-congruent spending, financial distress moderates the relationship between self-congruent spending and happiness (Chapter 7). These findings contribute insights into how consumption patterns are related to consumer attributes and usefulness for personalisation in marketing, as well as policy recommendations for improving well-being by targeting consumption patterns in financially distressed individuals. In addition, this thesis also showcases the value of machine learning and large-scale behavioural field data in the study of consumer psychology. Privacy and ethical concerns surrounding automated profiling and microtargeting are also cautioned

Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges