A Taxonomy of Web Personalization

Web personalization has become an important way to provide individualized user experiences. As a fragmented use of the term “Web personalization” and a lack of a common framework potentially hinder the establishment of a cumulative body of research, we develop a taxonomy of Web personalization. Bringing together research from information systems, computer science, and marketing, we develop a taxonomy focusing on the meta-characteristics user modeling (with the dimensions type of data, acquisition method, and life span of data) and system adaptation (with the dimensions object, volatility, scope, and control of adaptation). We demonstrate an application of our taxonomy by analyzing a sample of articles published in premier information systems journals and present some exemplary use cases to demonstrate how the taxonomy could be applied in practical contexts

Quality of experience aware adaptive hypermedia system

The research reported in this thesis proposes, designs and tests a novel Quality of Experience Layer (QoE-layer) for the classic Adaptive Hypermedia Systems (AHS) architecture. Its goal is to improve the end-user perceived Quality of Service in different operational environments suitable for residential users. While the AHS’ main role of delivering personalised content is not altered, its functionality and performance is improved and thus the user satisfaction with the service provided. The QoE Layer takes into account multiple factors that affect Quality of Experience (QoE), such as Web components and network connection. It uses a novel Perceived Performance Model that takes into consideration a variety of performance metrics, in order to learn about the Web user operational environment characteristics, about changes in network connection and the consequences of these changes on the user’s quality of experience. This model also considers the user’s subjective opinion about his/her QoE, increasing its effectiveness and suggests strategies for tailoring Web content in order to improve QoE. The user related information is modelled using a stereotype-based technique that makes use of probability and distribution theory. The QoE-Layer has been assessed through both simulations and qualitative evaluation in the educational area (mainly distance learning), when users interact with the system in a low bit rate operational environment. The simulations have assessed “learning” and “adaptability” behaviour of the proposed layer in different and variable home connections when a learning task is performed. The correctness of Perceived Performance Model (PPM) suggestions, access time of the learning process and quantity of transmitted data were analysed. The results show that the QoE layer significantly improves the performance in terms of the access time of the learning process with a reduction in the quantity of data sent by using image compression and/or elimination. A visual quality assessment confirmed that this image quality reduction does not significantly affect the viewers’ perceived quality that was close to “good” perceptual level. For qualitative evaluation the QoE layer has been deployed on the open-source AHA! system. The goal of this evaluation was to compare the learning outcome, system usability and user satisfaction when AHA! and QoE-ware AHA systems were used. The assessment was performed in terms of learner achievement, learning performance and usability assessment. The results indicate that QoE-aware AHA system did not affect the learning outcome (the students have similar-learning achievements) but the learning performance was improved in terms of study time. Most significantly, QoE-aware AHA provides an important improvement in system usability as indicated by users’ opinion about their satisfaction related to QoE

User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience

A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further step towards an iterative design that considers the user interaction a central point. The paper discusses how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the developments that followed that first experience: our findings seem still valid despite the passed time

Third international workshop on Authoring of adaptive and adaptable educational hypermedia (A3EH), Amsterdam, 18-22 July, 2005

The A3EH follows a successful series of workshops on Adaptive and Adaptable Educational Hypermedia. This workshop focuses on models, design and authoring of AEH, on assessment of AEH, conversion between AEH and evaluation of AEH. The workshop has paper presentations, poster session and panel discussions

Defining adaptive learning design templates for combining design and runtime adaptation in aLFanet

Adaptive features are expected to improve the effectiveness of the learning process in online learning. Nevertheless, most current adaptive sys-tems do not deal with combining design and runtime adaptations. To take ad-vantage of this combination a new adaptive iLMS based on standards, called aLFanet, is being developed. The system includes: (i) an authoring tool to de-velop courses IMS-LD compliant, (ii) an adaptive engine based on a multi-agent architecture which is intended to cope with several adaptive tasks for various types of users (learners, authors and tutors), (iii) a set of advanced pedagogical scenarios that combine design and runtime adaptations to make the authoring of these type of adaptive courses feasible. In this paper we focus on the types of adaptations and the process we have defined to facilitate the con-struction of the adaptive scenarios.EC 5th Framework IST-2001-3328

Virtual store atmosphere in internet retailing: Measuring virtual retail store layout effects on consumer buying behaviour

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The research presented in this dissertation is concerned with the effects of the "virtual store atmosphere" on consumer buying behaviour within the context of Internet retailing. More specifically, the focus of this research is to investigate whether the virtual store layout, as a major virtual store atmosphere determinant, affects consumer buying behaviour during shopping activity within a virtual grocery store over the Web. The present research is of a multidisciplinary nature and belongs to the field of Internet Retailing, in which there is not to date an exhaustive established theory available as the case is for conventional retailing. Therefore, the relevant literature covers the established theories in the areas of Marketing, Retailing and Consumer Behaviour along with current research in Internet retailing. Moreover, Human Computer Interaction (HCI) served as an important theoretical tool as far as Web site design principles and guidelines are concerned. The research hypotheses were mainly generated based on the conventional retail store layout literature review. They were tested through a laboratory experiment employing a causal research approach. To that end, a virtual retail laboratory store employing the three most common conventional retailing layouts (i.e., grid, freeform, and racetrack) was developed in three versions (i.e., one version per layout), following the concept and rules applied in each specific layout type. Therefore, the layout was the only manipulated variable (treatment), since all other potential influencing factors remained the same. The findings of the present study indicate that conventional retailing store layout theory is not applicable on its present form in the context of Internet retailing. Furthermore, the layout was found to affect consumer buying behaviour regarding "perceived usefulness towards searching for and buying shopping list products," "perceived ease of using the store," "perceived entertainment during shopping activity" and "time spent for shopping." However, it was found that the layout does not significantly affect "promotion effectiveness" and "impulse purchases." Based on the research findings, the "freegrid" layout (i.e., a new layout type) was introduced as an emerging layout for Internet retailing. The suggested layout contributes toward the Internet retailing theory development, as well as toward the provision of direct managerial implications. Finally, the present research provides several future research directions dealing with the virtual store atmosphere effects on consumer buying behaviour

Lightweight adaptive personalised e-advertising

Adaptation and personalisation is aimed at improving the user experience in e-systems. Personalisation was initially applied in the fields of distance learning and web-based educational systems. Adaptation can be also used in e-advertising, to increase customer satisfaction and encourage repeat visits to websites. Several models/frameworks have been designed for adaptation, for instance AHAM, LAOS, AdRosa, and MyAds. Many systems have been developed based on these frameworks. Most previous models/frameworks were primarily designed for personalised educational experience and were aimed at standalone systems, which cannot be (easily) integrated into existing websites in a lightweight manner. In addition, some of them are used in the portal model of advertising, since they match the interests of the publisher and the advertiser. The aim of this work is to overcome the limitations and weaknesses of these models and systems to deliver adaptive advertising. This work firstly attempts to support and facilitate the integration between adaptive systems and business websites. It also introduces a method to control and adapt advertisements located and owned by businesses. This thesis further proposes a generalised model, the Layered Adaptive Advertising Integration (LAAI), as the starting point for the development of an adaptive advertisement system. In a second stage, it presents a study that assesses the effectiveness of a system (AEADS) based on this model, via a trial run of a model prototype with users (both customers and business owners). In a third stage, social networks are used as inputs for the user model of customers, to enhance the efficiency of acquiring user information, as an addition to the user registration process. Furthermore, social interactions, such as the facility to use “like”, are added to the user model, and the delivery process has the ability to apply actions based on this data. Finally, an evaluation of the whole system proposed is conducted, with business owners and Internet users alike

Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning

Drachsler, H., Hummel, H. G. K., & Koper, R. (2009). Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning. Journal of Digital Information, 10(2), 4-24.The following article addresses open questions of the discussions in the first SIRTEL workshop at the EC-TEL conference 2007. It argues why personal recommender systems have to be adjusted to the specific characteristics of learning to support lifelong learners. Personal recommender systems strongly depend on the context or domain they operate in, and it is often not possible to take one recommender system from one context and transfer it to another context or domain. The article describes a number of distinct differences for personalized recommendation to consumers in contrast to recommendations to learners. Similarities and differences are translated into specific demands for learning and specific requirements for personal recommendation systems. It further suggests an evaluation approach for recommender systems in technology-enhanced learning.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org