Applying digital content management to support localisation

The retrieval and presentation of digital content such as that on the World Wide Web (WWW) is a substantial area of research. While recent years have seen huge expansion in the size of web-based archives that can be searched efficiently by commercial search engines, the presentation of potentially relevant content is still limited to ranked document lists represented by simple text snippets or image keyframe surrogates. There is expanding interest in techniques to personalise the presentation of content to improve the richness and effectiveness of the user experience. One of the most significant challenges to achieving this is the increasingly multilingual nature of this data, and the need to provide suitably localised responses to users based on this content. The Digital Content Management (DCM) track of the Centre for Next Generation Localisation (CNGL) is seeking to develop technologies to support advanced personalised access and presentation of information by combining elements from the existing research areas of Adaptive Hypermedia and Information Retrieval. The combination of these technologies is intended to produce significant improvements in the way users access information. We review key features of these technologies and introduce early ideas for how these technologies can support localisation and localised content before concluding with some impressions of future directions in DCM

Methods for adaptivity in intelligent web-based learning systems

There are two main methods for implementing adaptivity in intelligent web-based learning systems: adaptive presentation (or content-level adaptation) and adaptive navigation support (or link-level adaptation). In the systems that use an adaptive presentation method, the content of an adaptive hypermedia page is generated or assembled from pieces according to the user’s background and knowledge state. In such the page, narrowed and detailed deep information (in forms of multimedia or text) is provided for advanced users, while broader and less deep additional explanation is provided for novices. Adaptive navigation support is a method of helping users to find their paths of learning in hypermedia systems by adapting the way of presenting links to goals, knowledge, and preferences of individual users. It consists of all methods of altering visible links to support hyperspace navigation. Some technologies were distinguished from the points of view according to the way they adapt presentation of links: direct guidance, link sorting, link hiding, link annotation, link generation, and map adaptation. Based on recent research and applications, this simple taxonomy is developed further

A prototype tool for the automatic generation of adaptive websites

This paper presents AWAC, a prototype CAWE tool for the automatic generation of adaptive Web applications based on the A-OOH methodology. A-OOH (Adaptive OO-H) is an extension of the OO-H approach to support the modeling of personalized Websites. A-OOH allows modeling the content, structure, presentation and personalization of a Web Application. The AWAC tool takes the A-OOH design models of the adaptive Website to generate as an input. Once generated, the adaptive Website also contains two modules for managing the personalization which, at runtime, analyze the user browsing events and adapt the Website according to the personalization rule(s) triggered. These personalization rules are specified in an independent file so they can be updated without modifying the rest of the application logic

Incorporating learning styles into the user model

In this paper, we show the main definitions of learning styles, and a summary of the opinions about the efficacy of learning styles. In addition, this paper explores the application of the Felder-Silverman learning style model to adaptive training courses delivered via the “World Wide Web”. Due to the newness of the Web, its features, benefits, limitations and requirements as a delivery medium for distance learning are largely unstudied and unverified. This paper presents an attempt to incorporate learning styles in adaptive web-based systems and links it to the larger context of web-based education. In sum, this piece of research offers new ideas concerning an Adaptive We-based Education system, which includes the extraction of student’s learning styles preferences and then modifying the course presentation. We have implemented a prototype that adapts the course structure to the student learning style. We suggest the application of the results of the ILS questionnaire to automatically adapt some dimensions of the Felder-Silverman model to the course content and structure. The underlying idea of adaptive hypermedia based on learning styles is quite simple: adapt the presentation of course material so that it is more conductive to each student learning the course. This tailoring should allow for student learning in the shortest possible period of time. This approach has the effect of removing the impact of the instructor’s learning and eaching style and allowing the student to see the material through the clear lenses of his own perspective and learning style.The Spanish Interdepartmental Commission of Science and Technology (CICYT), project number TIC2001-0685-C02-01, has sponsored this work

Developing Adaptive and Personalized Mobile Applications: A Framework and Design Issues

The rapid growth of mobile technology has expedited ubiquitous information access via handheld devices. However, the fundamental natures of mobile information systems are different from those of desktop applications in terms of purpose of use, device features, communication networks, and working environments. This poses various challenges to mobile information systems on how to deliver and present multimedia content in an effective and adaptive manner. One of the major challenges is to deliver personalized information to the right person in a preferred format based on the changing environment. This paper proposes an innovative framework for developing mobile applications that deliver personalized, context-aware, and adaptive content to mobile users. The framework consists of four major components: information selection, content analysis, media transcoding, and customized presentation. It can be applied to a variety of mobile applications such as mobile web, news alert services, and mobile commerce

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

Integrated content presentation for multilingual and multimedia information access

For multilingual and multimedia information retrieval from multiple potentially distributed collections generating the output in the form of standard ranked lists may often mean that a user has to explore the contents of many lists before finding sufficient relevant or linguistically accessible material to satisfy their information need. In some situations delivering an integrated multilingual multimedia presentation could enable the user to explore a topic allowing them to select from among a range of available content based on suitably chosen displayed metadata. A presentation of this type has similarities with the outputs of existing adaptive hypermedia systems. However, such systems are generated based on “closed” content with sophisticated user and domain models. Extending them to “open” domain information retrieval applications would raise many issues. We present an outline exploration of what will form a challenging new direction for research in multilingual information access

Adaptive hypermedia for education and training

Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, Kühme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b)

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Personalization in cultural heritage: the road travelled and the one ahead

Over the last 20 years, cultural heritage has been a favored domain for personalization research. For years, researchers have experimented with the cutting edge technology of the day; now, with the convergence of internet and wireless technology, and the increasing adoption of the Web as a platform for the publication of information, the visitor is able to exploit cultural heritage material before, during and after the visit, having different goals and requirements in each phase. However, cultural heritage sites have a huge amount of information to present, which must be filtered and personalized in order to enable the individual user to easily access it. Personalization of cultural heritage information requires a system that is able to model the user (e.g., interest, knowledge and other personal characteristics), as well as contextual aspects, select the most appropriate content, and deliver it in the most suitable way. It should be noted that achieving this result is extremely challenging in the case of first-time users, such as tourists who visit a cultural heritage site for the first time (and maybe the only time in their life). In addition, as tourism is a social activity, adapting to the individual is not enough because groups and communities have to be modeled and supported as well, taking into account their mutual interests, previous mutual experience, and requirements. How to model and represent the user(s) and the context of the visit and how to reason with regard to the information that is available are the challenges faced by researchers in personalization of cultural heritage. Notwithstanding the effort invested so far, a definite solution is far from being reached, mainly because new technology and new aspects of personalization are constantly being introduced. This article surveys the research in this area. Starting from the earlier systems, which presented cultural heritage information in kiosks, it summarizes the evolution of personalization techniques in museum web sites, virtual collections and mobile guides, until recent extension of cultural heritage toward the semantic and social web. The paper concludes with current challenges and points out areas where future research is needed