Adaptivity & Personalization

The complexity of the current educational context, that is, the fragmentation of knowledge and the diversity which characterizes the students in our schools requires new competences. One of the answer is certainly to think about personalized path. The personalization of paths is a hard task for the teacher and, thus, the efficacy and also the sustainability of this choice need to be examined. For what concerns sustainability a solution has been provided by the interaction between the educational world and the world of knowledge engineering. The focus on the user, on intelligent systems for personalization, the adaptive and responsive design are proposals that were born with a different objective, but that have opened new perspectives also in the educational context. Besides, such processes have linked different research fields, the one of education and the one of knowledge engineering, such connection needs a common languages and meanings to be able to produce solutions. The paper i...

e widespread interest in interdisciplinarity is justi ed by a number of drivers, for example complex research which requires an integrated theoretical approach and complex problems whose solution is likely to come from di erent modes of participation through the support of a team of experts with di erent backgrounds. However, to integrate di erent perspectives and establish an interdisciplinary research approach or network and, thence develop an interdisciplinary understanding requires that several barriers on at least two macro-levels-institutional barriers linked to career opportunities and practical, procedural barriers related to communication and collaboration among experts from di erent elds-be overcome. A case study is described in which artefacts for the educational eld were created with the support of Arti cial Intelligence (AI) elements. is project illustrates many of the problematic issues connected with the development of research in interdisciplinary areas. Riassunto: L'interesse crescente verso i temi dell'interdisciplinarità è alimentato da una serie di motivazioni legate alla complessità della ricerca che richiede un approccio teorico integrato. La stretta collaborazione tra ricercatori ed esperti con di erenti background sembra essere la soluzione per risolvere problemi complessi. Ciò nonostante il processo di integrazione di diverse prospettive al ne di acquisire un approccio interdisciplinare e realizzare un gruppo di lavoro integrato che possa basarsi su una reciproca comprensione richiama alla necessità di superare ostacoli che si presentano a due macro livelli: barriere istituzionali, legate agli avanzamenti di carriera e barriere operative connesse alle modalità di comunicazione e interazione tra ricercatori che operano in campi di erenti. Viene descritto un caso di studio nel quale la creazione di artefatti in ambito educativo ha visto il supporto di elementi di Intelligenza Arti cale. Il progetto illustra molti dei nodi problematici connessi con lo sviluppo di ricerche in aree interdisciplinari.

We describe a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are presented to the user in a contextualised manner. Challenges and affordances of both adaptive and multilingual IR, with a particular focus on digital libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user's experience with online digital libraries.

This paper investigates issues of character believability and intelligent personalization through a reading of the Elder Scrolls: Oblivion. Oblivion's opening sequence simultaneously trains players in the function of the game, and allows them to customize their character class through the choices and actions they take. Oblivion makes an ambitious attempt at intelligent personalization in the character creation process. Its strategy is to track early gameplay decisions and "stereotype" players into one of 21 possible classes. This approach has two advantages over a less adaptive system. First, it supports the illusion of the gameworld as a real world by embedding the process of character creation within a narrativised gameplay context. Second, the intelligent recommendation system responds to the player's desire to believe that the game "knows" something about her personality. This leads the players to conceptualize the system as an entity with autonomous, human-like knowledge. This paper considers ways in which Oblivion both succeeds and fails at mapping player behaviour to appropriate class assignments. It does so through the analysis of multiple replayings of the opening sequence, and the application of two theoretical lenses-character believability and intelligent personalization. The paper documents moments where the dialogue between player and game breaks down, and argues for alternative techniques to customize the play experience within the desires of the player.

This paper describes a comprehensive framework giving support to a wide range of personalization facilities in a multimedia content management environment. The framework builds upon a rich, ontology-based representation of the domain of discourse, whereby content semantics are linked to a rich representation of user preferences. The expressive power of ontologies is used to develop automatic learning capabilities, in order to update user profiles as users interact with the system. The resulting descriptions of user ...

Persuasive Technology (PT) is an emerging, interdisciplinary research field, focusing on the design, development and evaluation of technologies aimed at creating awareness and inducing behavior change with the ultimate goal to increase wellbeing and quality of life. Academic researchers, designers, and practitioners from the social sciences and technological disciplines, as well as from the fields of health, healthcare, safety, sustainability, and ICT have developed this field in the preceding years, giving rise to a community which aims to 'persuade' people into adopting healthier lifestyles, behave more safely, and reduce consumption of renewable resources, to name a few examples. The 'technology' component in PT reflects usage of, amongst others, big data analytics, sensor technology for monitoring, personalized feedback and coaching, mHealth, data visualization techniques, serious gaming, and social media. The 12th International Conference on Persuasive Technologies was hosted by the Centre for eHealth &

Existing context-aware adaptation techniques are limited in their support for user personalization. There is relatively less developed research involving adaptive user modeling for user applications in the emerging areas of mobile and pervasive computing. This paper describes the creation of a User Profile Ontology for context-aware application personalization within mobile environments. We analyze users' behavior and characterize users' needs for context-aware applications. Special emphasis is placed in the ontological modeling of dynamic components for use in adaptable applications. We illustrate the use of the model in the context of a case study, focusing on providing personalized services to older people via smart-device technologies.

In t ro d u ct io n Acceptance is a key factor in user profiling. It consists of several dimensions: acceptance by users, acceptance by organisations and acceptance of the technology. The most important is user acceptance; it is a prerequisite for user profiling that the user allows a user profile to be built, just as he or she must be willing to accept the user profile to be used. In addition, in cross-domain settings the user must be willing to allow data to be exchanged between organisations from different sectors or domains.

Although clustering under constraints is a current research topic, a hierarchical setting, in which a hierarchy of clusters is the goal, is usually not considered. This paper tries to fill this gap by analyzing a scenario, where constraints are derived from a hierarchy that is partially known in advance. This scenario can be found, e.g., when structuring a collection of documents according to a user specific hierarchy. Major issues of current approaches to constraint based clustering are discussed, especially towards the hierarchical setting. We introduce the concept of hierarchical constraints and continue by presenting and evaluating two approaches using them. The approaches cover the two major fields of constraint based clustering, i.e. instance and metric based constraint integration. Our objects of interest are text documents. Therefore, the presented algorithms are especially fitted to work for these where necessary. Despite showing the properties and ideas of the algorithms in general, we evaluated the case of constraints that are unevenly scattered over the instance space, which is very common for real-world problems but not satisfyingly covered in other work so far.

The web community is witnessing an increase in the amount of available multilingual content and the number of multilingual web users. With this variety, personalized search systems are needed to connect people with relevant content, regardless of the language in which the content is provided, and taking into consideration the user's language capabilities and preferences. Therefore, search personalization algorithms should be developed with the aspect of multilinguality in mind, part of which involves understanding the effect of personalization algorithms on the user's search experience. This leads to an important question: given that users come from different linguistic backgrounds and have different language preferences, would personalization benefit all search users in the same way? This paper addresses this question by conducting an experiment to: (1) evaluate the effectiveness of the multilingual personalization algorithms (multilingual user modeling and multilingual result adaptation); and (2) determine whether multilingual personalization algorithms achieve the same degree of effectiveness for users who have different language preferences.

This paper describes a comprehensive framework giving support to a wide range of personalization facilities in a multimedia content management environment. The framework builds upon a rich, ontology-based representation of the domain of discourse, whereby content semantics are linked to a rich representation of user preferences. The expressive power of ontologies is used to develop automatic learning capabilities, in order to update user profiles as users interact with the system. The resulting descriptions of user interests in terms of ontologies are exploited, along with available content metadata, to provide users with personalized content search, browsing, ranking, and retrieval. On a wider perspective, the framework is built as an open platform that provides for further user and device adaptive capability extensions.

It is a common fact that modern e-learning schemes lack educational content representation and user personalisation. In this framework, automated extraction of user profiles, to be used in an e-learning content offering system, forms an interesting and important problem. In this approach we present the design and implementation of such a profile-based system, by which content is matched to its environmental context, so that it can be adapted to its user's needs and capabilities. Current effort extends previous work on profile extraction via clustering techniques and on integrated e-learning systems. It relies on the fundamental IEEE e-learning model, suitably adapted to reflect and focus on profiling aspects of the system.

It is a common fact that modern e-learning schemes lack educational content representation and user personalisation. In this framework, automated extraction of user profiles, to be used in an e-learning content offering system, forms an interesting and important problem. In this approach we present the design and implementation of such a profile-based system, by which content is matched to its environmental context, so that it can be adapted to its user's needs and capabilities. Current effort extends previous work on profile extraction via clustering techniques and on integrated e-learning systems. It relies on the fundamental IEEE e-learning model, suitably adapted to reflect and focus on profiling aspects of the system.

A growing number of applications for the Semantic Web are expected to be able to address user preferences in addition to well defined constraints when searching through large volumes of linked data. SPARQL, the most popular language for querying linked data repositories, does not have built-in tools for representing and processing preferences. The need for more adequate expression of user queries is well recognized by the Semantic Web community and two main approaches were offered to address this need. The quantitative approach associates a scoring function with each query result allowing results to be ordered according to their relevance to user preferences, while the qualitative approach relies on extending SPARQL with modifiers to express and rank preferences. The major concern with the former is that numerical scoring functions are hard to define, while the later cannot handle multiple preferences at the same time. In this paper, we suggest utilizing domain knowledge to process and rank SPARQL query results according to user preferences without the need to modify SPARQL functionality. An example application is used throughout the paper to illustrate the proposed approach.

The new educational approaches, as far as teaching of history in secondary education is concerned, are characterized by a shift away from sterile memorization and towards a critical approach of historical facts and phenomena; the aim is to contribute to both the development of students' historical concept and conscience and the promotion of critical thought. These teaching goals are pursued by promoting initiative of the students through self study assignments in the form of projects; students can be greatly supported in such tasks by computer-based applications, which can offer access to vast amounts of historical texts and data to be used next to the main scholar textbook and be analyzed by students. Still, existing applications seem to be quite inadequate for this purpose, as they require that the student be already informed on a matter, before the initiation of a quest for data. In this paper, we describe an intelligent information system that is designed to facilitate browsing of educational material and historical sources, thus allowing students to efficiently retrieve information on topics that are not yet known to them and expand in this way their historical knowledge. This can help in fulfilling the aforementioned teaching goals. Our system relies on the notion of the Electronic Road.

Constrained clustering received a lot of attention in the last years. However, the widely used pairwise constraints are not generally applicable for hierarchical clustering, where the goal is to derive a cluster hierarchy instead of a flat partition. Therefore, we propose for the hierarchical setting-based on the ideas of pairwise constraints-the use of must-link-before (MLB) constraints. In this paper, we discuss their properties and present an algorithm that is able to create a hierarchy by considering these constraints directly. Furthermore, we propose an efficient data structure for its implementation and evaluate its effectiveness with different datasets in a text clustering scenario.

Personalized multimedia access aims at enhancing the retrieval process by complementing explicit user requests with implicit user preferences. We propose and discuss the benefits of the introduction of ontologies for an enhanced representation of the relevant knowledge about the user, the context, and the domain of discourse, as a means to enable improvements in the retrieval process and the performance of adaptive capabilities. We develop our proposal by describing techniques in several areas that exemplify the explotation of the richness and power of formal and explicit semantics descriptions, and the improvements therein.

Promptness, efficiency and stickiness are among the advantages exhibited by the new crop of Rich Internet Applications (RIAs). These advantages came at the cost of increasing the complexity of development. Additionally, the plethora of RIA frameworks can lock this code into a specific platform. This scenario advises for using model-driven development (MDD). This paper focuses on interactionrich RIAs by addressing two issues: (1) interaction dependencies among widgets, and (2) grouping of widgets into Ajax pages. These concerns are captured in the Orchestration Model. MDD wise, OO-H metamodels accounts for the PIMs whereas Google Web Toolkit is the selected PSM. During transformation, a "message broker" pattern is introduced to decouple widgets from their dependencies. When Ajax pages are generated, heuristics are introduced to find a balance between communication overhead, presentation readiness and maintainability. A running example is used throughout.

Recent advances in wireless networking technologies and the growing success of mobile computing devices are enabling new classes of applications. Distributed applications running in a mobile environment are often subject to varying qualities of service from the underlying infrastructure. The objective of the work outlined in this research is the development of an Ambient Middleware framework for Context-awareness which will offer new opportunities for application developers. Context-awareness has been a central issue in Ambient Intelligent research for the last decade. Ambient Intelligent systems and applications represent extremely complex and heterogeneous distributed systems, composed of hardware and software, and the need for middleware for seamless integration is well recognised. Research shows that existing middleware solutions need to evolve, thus permitting the dissemination of omnipresent attributes within the Ubiquitous and Pervasive computing environments of today. To det...

Hera is a model-driven methodology for designing Semantic Web Information Systems (SWIS). Based on the principle of separation-of-concerns, Hera defines models to describe the different aspects of a SWIS. These models are represented using RDF, the foundation language of the Semantic Web. Hera is composed of two phases: the data collection phase, which integrates data from different sources, and the presentation generation phase, which builds a hypermedia presentation for the integrated data. The focus of this paper is on the hypermedia presentation generation phase and the associated model specifications. The Hera presentation generation phase has two variants: a static one that computes at once a full Web presentation, and a dynamic one that computes one-page-at-a-time by letting the user influence the next Web page to be presented. The dynamic variant proposes, in addition to the models from the static variant, new models to capture the data resulted from the user's interaction with the system. The implementation is based on a sequence of data transformations applied to the Hera models that eventually produces a hypermedia presentation.

Promptness, efficiency and stickiness are among the advantages exhibited by the new crop of Rich Internet Applications (RIAs). These advantages came at the cost of increasing the complexity of development. Additionally, the plethora of RIA frameworks can lock this code into a specific platform. This scenario advises for using model-driven development (MDD). This paper focuses on interactionrich RIAs by addressing two issues: (1) interaction dependencies among widgets, and (2) grouping of widgets into Ajax pages. These concerns are captured in the Orchestration Model. MDD wise, OO-H metamodels accounts for the PIMs whereas Google Web Toolkit is the selected PSM. During transformation, a "message broker" pattern is introduced to decouple widgets from their dependencies. When Ajax pages are generated, heuristics are introduced to find a balance between communication overhead, presentation readiness and maintainability. A running example is used throughout.

Aspect orientation offers an intuitive way to specifiy adaptivity for web applications, but despite its advantages, the approach still lacks acceptance. We argue that there are two main reasons for this: First, aspects make implicit assumptions on the underlying system and can thus produce invalid behavior if that system is changed. Second, the lack of concepts for dealing with aspect interactions places a heavy burden on the use of multiple aspects. In this paper we discuss how Hyper-Adapt addresses these problems, paving the road towards a productive use of aspect orientation in the domain of web applications.

Adaptation addresses the complexity and overload caused by an increasing amount of available resources by the identification and presentation of relevant resources. Drawbacks of existing approaches to this end include the limited degree of customization, difficulties in the acquisition of model information and the lack of control and transparency of the system's adaptive behavior. This paper proposes an approach which addresses these drawbacks to perform meaningful and effective adaptation by the application of semantic web technologies. This comprises the use of an ontology and adaptation rules for knowledge representation and inference engines for reasoning. The focus of this paper lies in the presentation of adaptation rules.

In this paper, we investigate how the Semantic Web can enhance web navigation and accessibility by following a hybrid approach of document-oriented and data-oriented considerations. Precisely, we propose a methodology for specifying, extracting, and presenting semantic data embedded in (X)HTML documents with RDFa in order to enable and improve ubiquitous web navigation and accessibility for end-users. In our context, embedded data does not only contain data type property annotations, but also object properties for interlinking, and embedded domain knowledge for enhanced content navigation through ontology reasoning. We provide a prototype implementation, called Semantic Web Component (SWC) and evaluate our methodology along a concrete scenario for mobile devices and with respect to precision, performance, network traffic, and usability. Evaluation results suggest that our approach decreases network traffic as well as the amount of information presented to a user without requiring significantly more processing time, and that it allows creating a satisfactory navigation experience.

In the past, several automatic video summarization systems had been proposed to generate video summary. However, a generic video summary that is generated based only on audio, visual and textual saliencies will not satisfy every user. This paper proposes a novel system for generating semantically meaningful personalized video summaries, which are tailored to the individual user's preferences over video semantics. Each video shot is represented using a semantic multinomial which is a vector of posterior semantic concept probabilities. The proposed system stitches video summary based on summary time span and top-ranked shots that are semantically relevant to the user's preferences. The proposed summarization system is evaluated using both quantitative and subjective evaluation metrics. The experimental results on the performance of the proposed video summarization system are encouraging.

With the availability of GPS receivers in more and more mobile handsets, location sharing has become the next mobile killer-app. Services like Google Latitude or Yahoo's FireEagle are used by thousands of subscribers to share their current location in real-time with their family, their friends, or even publish it online, while Sense Network's CitySense application uses live movement traces from entire metropolitan areas to show users the "most popular places" in the city. Even though research in location privacy has proposed a range of solutions for safeguarding location information, it is unclear how existing proposals can be applied to such applications. In this paper, we set forth a categorization of location sharing applications, outline the various privacy challenges each category poses, and discuss the shortcomings of existing solutions.

Thanks to the development of new technologies (such as PCs, PDAs, digital cameras, etc.) and with the advent of the Web, people are faced to deal with an increasing amount of information during their every day-life activities. As a consequence, the problem of finding the right information, at the right time, in a short period of time, becomes more and more crucial. Several technologies such as semantic web data mining and interactive visualizations are nowadays available to address these specific issues. However they have not been jointly exploited. With this respect, the paper presents a novel approach. Finally a prototype that validate our approach is presented.

Rich Internet Applications offer Web surfers a richer user experience, mainly due to better responsiveness and enhanced user interface capabilities. In recent years, existing design methodologies targeting traditional Web 1.0 applications were extended to also support RIAs. These extensions do not yet cover all design concerns typically encountered in state-of-the-art Web applications. One yet unsupported aspect is the personalization of content and presentation to the specific user and his/her context, exploiting the extra capabilities offered by RIAs. This article addresses this hiatus and presents an extension of the OOH4RIA approach to include presentation personalization support, focusing on Rich Internet Applications.

Web engineering methods provide a systematic approach to develop complex and high quality Web applications. Many of these methods provide, in some way, personalization support. However, none of the existing Web methodologies provide a tool which allow the modeling, automatic generation and deployment of personalized Web applications in a complete way. In this line, they also do not exist tools which allow the designer modifying the personalization strategies at runtime, avoiding to regenerate Web applications from scratch. To tackle these lacks, in this paper we have presented a tool that has been developed to give support to the A-OOH (Adaptive Object Oriented Hypermedia) design method. The main advantages of this tool are the automatic generation and deployment of personalized Web applications with personalization support at runtime.

More and more, mobile devices act as personal information managers and are able to obtain rich contextual information on the user's environment. Mobile, context-aware web applications can exploit this information to better address the needs of mobile users. Currently, such websites are either developed separately from their associated desktop-oriented version, or both versions are created simultaneously by employing methodologies that support multiplatform context-aware websites, requiring an extensive engineering effort. While these approaches provide a solution for developing new websites, they go past the plethora of existing websites. To address this issue, we present an approach for enhancing existing websites on-the-fly with context-aware features. We first discuss the requirements for such an adaptation process, and identify applicable adaptation methods to realize context-aware features. Next, we explain our generic approach, which is grounded in the use of semantic information extracted from existing websites. Finally, we present a concrete application of our approach that is based on the SCOUT framework for mobile and context-aware application development.

Personalization is desirable, but writing the adaptation behaviour description to go with it is taxing. Even more challenging is the application of multiple adaptation strategies over the same static content. This paper focuses on recent work on strategy modularisation and merger development in the authoring process ofadaptive hypermedia. The reason for the modularisation of strategies is to break a complex adaptation decision into a number of simpler ones, which may be reused more easily and applied in different orders. The rationale for strategy merger is to be able to apply multiple adaptation strategies over the same content - a challenge which is not yet fully addressed in current adaptive hypermedia systems. To demonstrate the proposed method we present an example case study and sample strategies written in the LAG adaptation language. The case study is based on a recently proposed model for Quality of Experience in e-learning. This model exposes the complex interaction betwee...

The new educational approaches, as far as teaching of history in secondary education is concerned, are characterized by a shift away from sterile memorization and towards a critical approach of historical facts and phenomena; the aim is to contribute to both the development of students' historical concept and conscience and the promotion of critical thought. These teaching goals are pursued by promoting initiative of the students through self study assignments in the form of projects; students can be greatly supported in such tasks by computer-based applications, which can offer access to vast amounts of historical texts and data to be used next to the main scholar textbook and be analyzed by students. Still, existing applications seem to be quite inadequate for this purpose, as they require that the student be already informed on a matter, before the initiation of a quest for data. In this paper, we describe an intelligent information system that is designed to facilitate browsing of educational material and historical sources, thus allowing students to efficiently retrieve information on topics that are not yet known to them and expand in this way their historical knowledge. This can help in fulfilling the aforementioned teaching goals. Our system relies on the notion of the Electronic Road.

Computer-based education has already been acknowledged as an important asset for medical education. For example, web-based educational systems for medicine and health provide an additional important advantage to remote learners through platform-and time-independence. However, such systems are difficult to create as they require a lot of effort from both medical tutors and software engineers. Therefore, repetition of effort has to be avoided and such systems should be able to be used to their full extent from whoever requires medical and health knowledge on the specific topics. This means that they need to incorporate intelligent techniques in order to be able to adapt dynamically to the needs of individual users rather than have many static educational systems designed solely for different kinds of users. In view of this, in this paper we address the problem of developing an adaptive e-learning system for the medical domain of Atheromatosis. Atheromatosis of the aortic arch has been recognized as an important source of embolism, which is a frequent cause of stroke. This is the main reason that the particular topic is of interest to a wide range of users with different background knowledge and needs (e.g. medical students, nurses, common people interested in maintaining a good health, etc.). The inference mechanism of the system uses a combination of rule-based reasoning and a decision making theory. In order to design the reasoning mechanism of the system, and thus incorporate the decision making theory successfully, we conducted an empirical study. The empirical study involved distribution of questionnaires to several classes of potential users of an e-learning system about Atheromatosis and analysis of the results by computer and medical experts. The results of the empirical study were used for designing the reasoning mechanism of the system.

We describe a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents are presented to the user in a contextualised manner. Challenges and affordances of both adaptive and multilingual IR, with a particular focus on digital libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user's experience with online digital libraries.

Obesity has become a major societal problem worldwide [1][2]. The main reason for severe overweight is excessive intake of energy, in relation to the individual needs of a human body. Obesity is associated with poor eating habits and/or a sedentary lifestyle. A significant part of the obese population (40%) belongs to a vulnerable target group of emotional eaters, who overeat due to negative emotions [3]. There is a need for self-management support and personalized coaching to enhance emotional eaters in recognising and self-regulating their emotions. Over the last years, coaching systems have been developed for behavior change support, healthy lifestyle, and physical activity support [4]-[9]. Existing virtual coach applications lack systematic evaluation of coaching strategies and usually function as (tele-)monitoring systems. They are limited to giving general feedback to the user on achieved goals and/or accomplished (online) assignments. Dialectical Behavior Therapy (DBT) focuse...

Abstract. Traditionally, pervasive systems are designed with a focus on the individual, offering services that take advantage of their physical environment and provide a context-aware, personalised user experience. On the other hand, social computing is centred around the notion of a community, leveraging the information about the users and their social relationships, connecting them together often using different criteria that can range from a user’s physical location and activity to personal interests and past experiences. The SOCIETIES Integrated Project attempts to bridge these different technologies in a unified platform allowing individuals to utilise pervasive services in a community sphere. SOCIETIES aims to use community driven context awareness, preference learning and privacy protection for intelligently connecting people, communities and things. Thus, the goal of SOCIETIES is to radically improve the utility of Future Internet services by combining the benefits of pervas...

Over the last years adaptive Web personalization has be-come a widespread service and all the major players of the WWW are providing it in various forms. Ephemeral personalization, in particular, deals with short time interests which are often tacitly entailed from user browsing behaviour or contextual information. Such personalization can be found almost anywhere in the Web in several forms, ranging from targeting advertising to automatic language localisation of content. In order to present personalized content a user model is typically built and maintained at server-side by collecting, explicitly or implicitly, user data. In the case of ephemeral personalization this means storing at server-side a huge amount of user behaviour data, which raises severe privacy con-cerns. The evolution of the semantic Web and the growing availability of semantic metadata embedded in Web pages allow a role reversal in the traditional personalization scenario. In this paper we present a novel approa...

Research has shown that there are differences in how males and females respond to persuasive attempts. This paper examines the persuasiveness of the six persuasive strategies-Reciprocity, Scarcity, Authority, Commitment and Consistency, Consensus and Liking developed by Cialdini with respect to age and gender. The results of the large-scale study (N = 1108) show that males and females differ significantly in their responsiveness to the strategies. Overall, females are more responsive to most of the strategies than males and some strategies are more suitable for persuading one gender than the other. The results of our study also reveal some differences between younger adults and adults with respect to the persuasiveness of the strategies. Finally, the results show that irrespective of gender and age, there are significant differences between the strategies regarding their perceived persuasiveness overall, shedding light on the comparative effectiveness of the strategies.

To realise an Ambient Intelligence environment, it is paramount that applications can dispose of information about the context in which they operate, preferably in a very general manner. For this purpose various types of information should be assembled to form a representation of the context of the device on which aforementioned applications run. To allow interoperability in an Ambient Intelligence environment, it is necessary that the context terminology is commonly understood by all participating devices. In this paper we propose an adaptable and extensible context ontology for creating context-aware computing infrastructures, ranging from small embedded devices to high-end service platforms. The ontology has been designed to solve several key challenges in Ambient Intelligence, such as application adaptation, automatic code generation and code mobility, and generation of device specific user interfaces.

This article evaluates more than a dozen vocabulary learning techniques for students of a second or foreign language. These techniques are divided into four broad categories: decontextualizing, semi-contextualizing, fully contextualizing, and adaptable. Each technique is evaluated in terms of underlying theoretical assumptions and practical utility. Specific classroom implications are also offered.

Promptness, efficiency and stickiness are among the advantages exhibited by the new crop of Rich Internet Applications (RIAs). These advantages came at the cost of increasing the complexity of development. Additionally, the plethora of RIA frameworks can lock this code into a specific platform. This scenario advises for using model-driven development (MDD). This paper focuses on interactionrich RIAs by addressing two issues: (1) interaction dependencies among widgets, and (2) grouping of widgets into Ajax pages. These concerns are captured in the Orchestration Model. MDD wise, OO-H metamodels accounts for the PIMs whereas Google Web Toolkit is the selected PSM. During transformation, a "message broker" pattern is introduced to decouple widgets from their dependencies. When Ajax pages are generated, heuristics are introduced to find a balance between communication overhead, presentation readiness and maintainability. A running example is used throughout.