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This paper discusses accuracy in processing ratings of and recommendations for item features. Such processing facilitates featurebased user navigation in recommender system interfaces. Item features, often in the form of tags, categories or meta-data, are becoming important hypertext components of recommender interfaces. Recommending features would help unfamiliar users navigate in such environments. This work explores techniques for improving feature recommendation accuracy. Conversely, it also examines possibilities for processing user ratings of features to improve recommendation of both features and items. This work’s illustrative implementation is a web portal for a museum collection that lets users browse, rate and receive recommendations for both artworks and interrelated topics about them. Accuracy measurements compare proposed techniques for processing feature ratings and recommending features. Resulting techniques recommend features with relative accuracy. Analysis indicates that processing ratings of either features or items does not improve accuracy of recommending the other.

The SMIL 3.0 language is the W3C's standard language for web-based multimedia. This book provides a comprehensive guide to all of SMIL's elements and attributes for all versions, from the complete SMIL Language profile to SMIL Tiny. Driven by dozens of examples and illustrated code fragments, every aspect of SMIL is treated in this book. Starting with essential background on XML and the streaming media infrastructure, this book considers recent features such as smilText and smilState, as well as the structuring, layout and timing aspects required to master SMIL. In addition, the book describes advanced SMIL functionality, including transitions, animation and embedded metadata, all from an application-oriented perspective.

Web 2.0 enables increased access to the museum digital collection. More and more, users will spend time preparing their visits to the museums and reflecting on them after the visits. In this context, the CHIP (Cultural Heritage Information Personalization) project offers tools to the users to be their own curator, e.g. planning a personalized museum tour, discovering interesting artworks they want to see in a 'virtual' or a 'real' tour and quickly finding their ways in the museum. In this paper we present the new additions to the CHIP tools, which target the above functionality - a Web-based Tour Preparation Wizard and an export of a personalized tour to an interactive Mobile Guide used in the physical museum space. In addition, the user interactions during a real museum visit are stored and synchronized with the user model, which is maintained at the museum Web site.

Web 2.0 enables increased access to the museum digital collection. More and more, users will spend time preparing their visits to the museums and reflecting on them after the visits. In this context, the CHIP (Cultural Heritage Information Personalization) project offers tools to the users to be their own curator, e.g. planning a personalized museum tour, discovering interesting artworks they want to see in a 'virtual' or a 'real' tour and quickly finding their ways in the museum. In this paper we present the new additions to the CHIP tools, which target the above functionality - a Web-based Tour Preparation Wizard and an export of a personalized tour to an interactive Mobile Guide used in the physical museum space. In addition, the user interactions during a real museum visit are stored and synchronized with the user model, which is maintained at the museum Web site.

This article presents the CHIP demonstrator1 for providing personalized access to digital museum collections. It consists of three main components: Art Recommender, Tour Wizard, and Mobile Tour Guide. Based on the semantically enriched Rijksmuseum Amsterdam2 collection, we show how Semantic Web technologies can be deployed to (partially) solve three important challenges for recommender systems applied in an open Web context: (1) to deal with the complexity of various types of relationships for recommendation inferencing, where we take a content-based approach to recommend both artworks and art-history topics; (2) to cope with the typical user modeling problems, such as cold-start for first-time users, sparsity in terms of user ratings, and the efficiency of user feedback collection; and (3) to support the presentation of recommendations by combining different views like a historical timeline, museum map and faceted browser. Following a user-centered design cycle, we have performed two evaluations with users to test the effectiveness of the recommendation strategy and to compare the different ways for building an optimal user profile for efficient recommendations. The CHIP demonstrator received the Semantic Web Challenge Award (third prize) in 2007, Busan, Korea.

The increasing availability of (digital) cultural heritage artefacts offers great potential for increased access to art content, but also necessitates tools to help users deal with such abundance of information. User-adaptive art recommender systems aim to present their users with art content tailored to their interests. These systems try to adapt to the user based on feedback from the user on which artworks he or she finds interesting. Users need to be able to depend on the system to competently adapt to their feedback and find the artworks that are most interesting to them. This paper investigates the influence of transparency on user trust in and acceptance of content-based recommender systems. A between-subject experiment (N = 60) evaluated interaction with three versions of a content-based art recommender in the cultural heritage domain. This recommender system provides users with artworks that are of interest to them, based on their ratings of other artworks. Version 1 was not transparent, version 2 explained to the user why a recommendation had been made and version 3 showed a rating of how certain the system was that a recommendation would be of interest to the user. Results show that explaining to the user why a recommendation was made increased acceptance of the recommendations. Trust in the system itself was not improved by transparency. Showing how certain the system was of a recommendation did not influence trust and acceptance. A number of guidelines for design of recommender systems in the cultural heritage domain have been derived from the study's results.

In this paper we present the CHIP demonstrator aimed at helping users to explore the Rijksmuseum Amsterdam collection both online and inside the museum. Cultural heritage data from various external sources is integrated to provide an enriched semantic knowledge structure. The resulting RDF/OWL graph is the basis for CHIP main functionality for recommendations, search and personalized interaction.

This paper describes ongoing work exploring aspects of personalized access to and presentation of virtual museum collections. The project demonstrator illustrates an interactive approach to collecting data about museum visitors in terms of their interests in and preferences about artefacts from the Rijksmuseum collection. This data is stored in user profiles used further to recommend routes through the museum and to guide the users towards artefacts related to their interests and preferences. The overall goal of the project is to explore different users' characteristics and personalize users' museum experiences within the Rijksmuseum virtual and physical collections.

This paper describes how the combination of recommendation and Semantic Web techniques can enhance user interaction with digital cultural heritage collections. The interface that this paper describes adapts user interaction to individual interest in both artworks and abstract concepts related to them. This paper presents an overview of several studies that evaluate a recommender system for museum collections. The findings and requirements derived from them form a basic framework for personalized exhibition tours that present multiple cultural artifacts as a structured and cohesive whole.

In this paper we present an approach for personalized access to museum collections. We use a RDF/OWL specification of the Rijksmuseum Amsterdam collections as a driver for an interactive dialog. The user gives his/her judgment on the artefacts, indicating likes or dislikes. The elicited user model is further used for generating recommendations of artefacts and topics. In this way we support exploration and discovery of information in museum collections. A user study provided insights in characteristics of our target user group, and showed how novice and expert users employ their background knowledge and implicit interest in order to elicit their art preference in the museum collections.

User-adaptive information filters can be a tool to achieve timely delivery of the right information to the right person, a feat critical in crisis management. This paper ex

The SMIL 2.0 Language is the Web's solution for multimedia. This book provides a comprehensive guide to all of SMIL 2.0's elements and attributes for both desktop and mobile multimedia. Driven by dozens of examples and illustrated code fragments, every aspect of SMIL is treated. This book considers the document structure, media integration, presentation layout and detailed timing constructs available in a wide range of SMIL compatible players and browsers.The book also considers advanced SMIL topics of linking, content control and SMIL animation, all from a practical, implementation-oriented perspective.

Much current research on hypermedia generation accepts user input only at the start of an otherwise fully automated process. However, since multimedia presentation creation is often a complex and creative process, it has multiple phases which would each benefit from human intervention. This paper presents a hypermedia generation model that lets the user influence all phases of this computer assisted human guided process. The main focus is on providing extra support for helping the user find relevant media items and combine them meaningfully into a rich and coherent multimedia presentation. Like fully automated systems, our approach uses explicit knowledge about the presentation's topic domain, narrative structures, hypermedia presentation and distinctions between media modalities. This paper presents a motivating scenario that is used to derive a number of system requirements and to discusses the pros and cons of the presented approach.

Semantic annotations of media repositories make relationships among the stored media and relevant concepts explicit. However, these relationships and the media they join are not directly presentable as hypermedia. Previous work shows how clustering over the annotations in the repositories can determine hypermedia presentation structure. Here we explore the application of different clustering techniques to generating hypermedia interfaces to media archives. This paper also describes the effect of each type of clustering on the end user's experience. We then generalize and unify these techniques with the use of proximity measures in further improving generated presentation structure

We generate hypermedia presentations from annotated media repositories using simple document structure as an intermediate phase. This poster applies Web style technologies to this process. Results include style specification for accessing semantically annotated media repositories, for determining document structure from semantic structure and for applying this document structure to the final presentation.

For humans to gain comprehensive views of large amounts of repository contents, they need to have insight into the relations among information objects. It is a challenge to automatically generate presentations of repository contents, through, for example, search results, which reveal such relations to readers. Such presentations must reflect properties of information objects such that large sets of information objects appear as a coherent whole. An approach to this is generation of discourse structures that convey such properties of information objects in presentations. Semantic Web technology provides a conceptual basis for generation of discourse in Web-based information environments. This paper describes automatic generation of sequence and emphasis in presentations of information objects. It shows generation of object sequences and emphasis

Generating hypermedia presentations requires processing constituent material into coherent, unified presentations. One large challenge is creating a generic process for producing hypermedia presentations from the semantics of potentially unfamiliar domains. The resulting presentations must both respect the underlying semantics and appear as coherent, plausible and, if possible, pleasant to the user. Among the related unsolved problems is the inclusion of discourse knowledge in the generation process. One potential approach is generating a discourse structure derived from generic processing of the underlying domain semantics, transforming this to a structured progression and then using this to steer the choice of hypermedia communicative devices used to convey the actual information in the resulting presentation. This paper presents the results of the first phase of the Topia project, which explored this approach. These results include an architecture for this more domain-independent processing of semantics and discourse into hypermedia presentations. We demonstrate this architecture with an implementation using Web standards and freely available technologies.

Time-based, media-centric Web presentations can be described declaratively in the XML world through the development of languages such as SMIL. It is difficult, however, to fully integrate them in a complete document transformation processing chain. In order to achieve the desired processing of data-driven, time-based, media-centric presentations, the text-flow based formatting vocabularies used by style languages such as XSL, CSS and DSSSL need to be extended. The paper presents a selection of use cases which are used to derive a list of requirements for a multimedia style and transformation formatting vocabulary. The boundaries of applicability of existing text-based formatting models for media-centric transformations are analyzed. The paper then discusses the advantages and disadvantages of a fully-fledged time-based multimedia formatting model. Finally, the discussion is illustrated by describing the key properties of the example multimedia formatting vocabulary currently implemented in the back-end of our Cuypers multimedia transformation engine.

The 'Document Web' has established itself through the creation of an impressive family of XML and related languages. In addition to this, the 'Semantic Web' is developing its own family of languages based primarily on RDF. Although these families were both developed specifically for 'the Web', each language family has been developed from different premises with specific goals in mind. The result is that combining both families in a single application is surprisingly difficult. This is unfortunate, since the combination of semantic processing with document processing provides advantages in both directions --- namely using semantic inferencing for more intelligent document processing and using document processing tools for presenting semantic representations to an end-user. In this paper, we investigate this integration problem, focusing on the role of (RDF) semantics in selecting, structuring and styling (XML) content. We analyze the approaches taken by two example architectures and use our analysis to derive a more integrated alternative.

Much current research on hypermedia generation accepts user input only at the start of an otherwise fully-automated process. However, since multimedia presentation creation is often a complex and creative process, it has multiple phases which would each benefit from human intervention. This paper presents a hypermedia generation model that lets the user influence all phases of this computer-assisted human-guided process. The main focus is on providing extra support for helping the user find relevant media items and combine them meaningfully into a rich and coherent multimedia presentation. Like fully-automated systems, our approach uses explicit knowledge about the presentation's topic domain, narrative structures, hypermedia presentation and distinctions between media modalities. This paper presents a motivating scenario that is used to derive a number of system requirements and to discuss the pros and cons of the presented approach.

The presentation generation area of hypermedia authoring contains different approaches to address the challenge of the presentation creation process. This paper presents the approach in which the author creates a presentation following the five stages process. These five stages reflect various facets in hypermedia authoring.