Peter Dolog

User Modeling, Adaptation, and Personalization

Interactive technologies pervade every aspect of modern life. Web sites, mobile devices, household gadgets, automotive controls, aircraft flight decks; everywhere you look, people are interacting with technologies. This trend is set to continue as we move towards a world comprising Smart Cities built around the Internet of Things. Unfortunately, much of the rhetoric surrounding this dawning age of ubiquitous and embedded computing fails to appropriately consider the people at the centre of it. These people are embodied social agents with motivations, emotions, capabilities, capacities, proclivities and predilections. Technological imaginings around the Internet of Things are often steeped in generalities or idealised scenarios of use. Such imaginings typically forget that design is always about meeting particular peoples’ needs in particular contexts. From concept to ideation to prototype and evaluation, the design of interactive technologies and systems that are intended for people should start with some understanding of who the users will be, what tasks and experiences they are aiming for, and what the circumstances, conditions or context(s) are at play. In this talk, I will discuss a simple people-centric framework devised with my colleagues and coauthors to inform the way we think about design, the ABCS of designing interactive systems. A descriptive guide rather than a prescriptive checklist, the framework draws on basic research in ergonomics, psychology and user modeling. It is intended to focus design thinking about people as the users of interactive, computational systems. It is intended to support us as the designers of interactive technologies as we scope, draft and iterate on the design space of imagined interactive experiences. Using examples from my own work, I will illustrate how this framework has been explicitly and/or tacitly applied in the design, development and evaluation of interactive, multimedia systems. In particular, I will consider how this framework is currently being applied to rethinking the concept of personalization.

Personalization in distributed e-learning environments

Personalized support for learners becomes even more important, when e-Learning takes place in open and dynamic learning and information networks. This paper shows how to realize personalized learning support in distributed learning environments based on Semantic Web technologies. Our approach fills the existing gap between current adaptive educational systems with well-established personalization functionality, and open, dynamic learning repository networks. We propose a service-based architecture for establishing personalized e-Learning, where personalization functionality is provided by various web-services. A Personal Learning Assistant integrates personalization services and other supporting services, and provides the personalized access to learning resources in an e-Learning network.

Current Trends in Web Engineering

Breach or lack of online privacy has become almost a commonplace of today’s digital age, mainly due to the inability of either enforcing privacy requirements or imposing strict sanctions against violations. The current state of affairs in data privacy is at a turning point for companies operating in EU state members as the enforcement of the General Data Protection Regulation (GDPR) empowers users with control over their personal data, including regulating its disclosure, withdrawing disclosure consent at any given time and tracking their data trail. Compliance with the GDPR is mandatory and it requires signifiant amendments and/or restructuring of data processing routines undertaken by enterprises. Currently, there is no framework to support the GDPR principles. This paper proposes privacyTracker, a GDPR-compliant framework that supports basic GDPR principles including data traceability and allowing a user to get a cryptographically verifiable snapshot of

The personal reader: Personalizing and enriching learning resources using semantic Web technologies

Traditional adaptive hypermedia systems have focused on providing adaptation functionality on a closed corpus, while Web search interfaces have delivered non-personalized information to users. In this paper, we show how we integrate closed corpus adaptation and global context provision in a Personal Reader environment. The local context consists of individually optimized recommendations to learning materials within the given corpus; the global context provides individually optimized recommendations to resources found on the Web, e. g., FAQs, student exercises, simulations, etc. The adaptive local context of a learning resource is generated by applying methods from adaptive educational hypermedia in a semantic web setting. The adaptive global context is generated by constructing appropriate queries, enrich them based on available user profile information, and, if necessary, relax them during the querying process according to available metadata.

A framework for browsing, manipulating and maintaining interoperable learner profiles

Learners are assessed by several systems during their life-long learning. Those systems can maintain fragments of information about a learner derived from his learning performance and/or assessment in that particular system. Customization services would perform better if they would be able to exchange as many relevant fragments of information about the learner as possible. This paper presents the conceptualization and implementation of a framework which provides a common base for the exchange of learner profiles between several sources. The exchange representation of learner profiles is based on standards. An API is designed and implemented to create/export and manipulate such learner profiles. The API is implemented for two cases, as a Java API and as web services with synchronized model exchange between multiple sources. Application cases of the API are discussed shortly as well.

A Scalable Approach for QoS-Based Web Service Selection

QoS-based service selection aims at finding the best component services that satisfy the end-to-end quality requirements. The problem can be modeled as a multi-dimension multi-choice 0-1 knapsack problem, which is known as NP-hard. Recently published solutions propose using linear programming techniques to solve the problem. However, the poor scalability of linear program solving methods restricts their applicability to small-size problems and renders them inappropriate for dynamic applications with run-time requirements. In this paper, we address this problem and propose a scalable QoS computation approach based on a heuristic algorithm, which decomposes the optimization problem into small sub-problems that can be solved more efficiently than the original problem. Experimental evaluations show that near-to-optimal solutions can be found using our algorithm much faster than using linear programming methods.

Semantic web technologies for the adaptive web

Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web provide conceptualization for the links which are a main vehicle to access information on the web. The subject domain ontologies serve as constraints for generating only those links which are relevant for the domain a user is currently interested in. Furthermore, user model ontologies provide additional means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components are crucial to be formalized by the semantic web ontologies for adaptive web. We use examples from an eLearning domain to illustrate the principles which are broadly applicable to any information domain on the web.

An environment for flexible advanced compensations of Web service transactions

Business to business integration has recently been performed by employing Web service environments. Moreover, such environments are being provided by major players on the technology markets. Those environments are based on open specifications for transaction coordination. When a failure in such an environment occurs, a compensation can be initiated to recover from the failure. However, current environments have only limited capabilities for compensations, and are usually based on backward recovery. In this article, we introduce an environment to deal with advanced compensations based on forward recovery principles. We extend the existing Web service transaction coordination architecture and infrastructure in order to support flexible compensation operations. We use a contract-based approach, which allows the specification of permitted compensations at runtime. We introduce abstract service and adapter components, which allow us to separate the compensation logic from the coordination logic. In this way, we can easily plug in or plug out different compensation strategies based on a specification language defined on top of basic compensation activities and complex compensation types. Experiments with our approach and environment show that such an approach to compensation is feasible and beneficial. Additionally, we introduce a cost-benefit model to evaluate the proposed environment based on net value analysis. The evaluation shows in which circumstances the environment is economical.

Personalizing access to learning networks

In this article, we describe a Smart Space for Learning#8482; (SS4L) framework and infrastructure that enables personalized access to distributed heterogeneous knowledge repositories. Helping a learner to choose an appropriate learning resource or activity is a key problem which we address in this framework, enabling personalized access to federated learning repositories with a vast number of learning offers. Our infrastructure includes personalization strategies both at the query and the query results level. Query rewriting is based on learning and language preferences; rule-based and ranking-based personalization improves these results further. Rule-based reasoning techniques are supported by formal ontologies we have developed based on standard information models for learning domains; ranking-based recommendations are supported through ensuring minimal sets of predicates appearing in query results. Our evaluation studies show that the implemented solution enables learners to find relevant learning resources in a distributed environment and through goal-based personalization improves relevancy of results.

Transactions Concurrency Control in Web Service Environment

Business transactions in Web service environments run with relaxed isolation and atomicity property. In such environments, transactions can commit and roll back independently on each other. Transaction management has to reflect this issue and address the problems which result for example from concurrent access to Web service resources and data. In this paper we propose an extension to the WS-transaction protocol which ensures the consistency of the data when independent business transactions access the data concurrently under the relaxed transaction properties. Our extension is based on transaction dependency graphs maintained at the service provider side. We have implemented such a protocol on top of WS-transaction. The extension on the Web service provider side is simple to achieve as it can be an integral part of the service invocation mechanism. It has also an advantage from an engineering point of view as it does not change the way consumers or clients of Web services have to be programmed. Furthermore, it avoids direct communication between transaction coordinators which preserves security by keeping the information about business transactions restricted to the coordinators which are responsible for them