Exploratory Browsing

In recent years the digital media has influenced many areas of our life. The transition from analogue to digital has substantially changed our ways of dealing with media collections. Today‟s interfaces for managing digital media mainly offer fixed linear models corresponding to the underlying technical concepts (folders, events, albums, etc.), or the metaphors borrowed from the analogue counterparts (e.g., stacks, film rolls). However, people‟s mental interpretations of their media collections often go beyond the scope of linear scan. Besides explicit search with specific goals, current interfaces can not sufficiently support the explorative and often non-linear behavior. This dissertation presents an exploration of interface design to enhance the browsing experience with media collections. The main outcome of this thesis is a new model of Exploratory Browsing to guide the design of interfaces to support the full range of browsing activities, especially the Exploratory Browsing. We define Exploratory Browsing as the behavior when the user is uncertain about her or his targets and needs to discover areas of interest (exploratory), in which she or he can explore in detail and possibly find some acceptable items (browsing). According to the browsing objectives, we group browsing activities into three categories: Search Browsing, General Purpose Browsing and Serendipitous Browsing. In the context of this thesis, Exploratory Browsing refers to the latter two browsing activities, which goes beyond explicit search with specific objectives. We systematically explore the design space of interfaces to support the Exploratory Browsing experience. Applying the methodology of User-Centered Design, we develop eight prototypes, covering two main usage contexts of browsing with personal collections and in online communities. The main studied media types are photographs and music. The main contribution of this thesis lies in deepening the understanding of how people‟s exploratory behavior has an impact on the interface design. This thesis contributes to the field of interface design for media collections in several aspects. With the goal to inform the interface design to support the Exploratory Browsing experience with media collections, we present a model of Exploratory Browsing, covering the full range of exploratory activities around media collections. We investigate this model in different usage contexts and develop eight prototypes. The substantial implications gathered during the development and evaluation of these prototypes inform the further refinement of our model: We uncover the underlying transitional relations between browsing activities and discover several stimulators to encourage a fluid and effective activity transition. Based on this model, we propose a catalogue of general interface characteristics, and employ this catalogue as criteria to analyze the effectiveness of our prototypes. We also present several general suggestions for designing interfaces for media collections

Semantically-enhanced recommendations in cultural heritage

In the Web 2.0 environment, institutes and organizations are starting to open up their previously isolated and heterogeneous collections in order to provide visitors with maximal access. Semantic Web technologies act as instrumental in integrating these rich collections of metadata by defining ontologies which accommodate different representation schemata and inconsistent naming conventions over the various vocabularies. Facing the large amount of metadata with complex semantic structures, it is becoming more and more important to support visitors with a proper selection and presentation of information. In this context, the Dutch Science Foundation (NWO) funded the Cultural Heritage Information Personalization (CHIP) project in early 2005, as part of the Continuous Access to Cultural Heritage (CATCH) program in the Netherlands. It is a collaborative project between the Rijksmuseum Amsterdam, the Eindhoven University of Technology and the Telematica Instituut. The problem statement that guides the research of this thesis is as follows: Can we support visitors with personalized access to semantically-enriched collections? To study this question, we chose cultural heritage (museums) as an application domain, and the semantically rich background knowledge about the museum collection provides a basis to our research. On top of it, we deployed user modeling and recommendation technologies in order to provide personalized services for museum visitors. Our main contributions are: (i) we developed an interactive rating dialog of artworks and art concepts for a quick instantiation of the CHIP user model, which is built as a specialization of FOAF and mapped to an existing event model ontology SEM; (ii) we proposed a hybrid recommendation algorithm, combining both explicit and implicit relations from the semantic structure of the collection. On the presentation level, we developed three tools for end-users: Art Recommender, Tour Wizard and Mobile Tour Guide. Following a user-centered design cycle, we performed a series of evaluations with museum visitors to test the effectiveness of recommendations using the rating dialog, different ways to build an optimal user model and the prediction accuracy of the hybrid algorithm. Chapter 1 introduces the research questions, our approaches and the outline of this thesis. Chapter 2 gives an overview of our work at the first stage. It includes (i) the semantic enrichment of the Rijksmuseum collection, which is mapped to three Getty vocabularies (ULAN, AAT, TGN) and the Iconclass thesaurus; (ii) the minimal user model ontology defined as a specialization of FOAF, which only stores user ratings at that time, (iii) the first implementation of the content-based recommendation algorithm in our first tool, the CHIP Art Recommender. Chapter 3 presents two other tools: Tour Wizard and Mobile Tour Guide. Based on the user's ratings, the Web-based Tour Wizard recommends museum tours consisting of recommended artworks that are currently available for museum exhibitions. The Mobile Tour Guide converts recommended tours to mobile devices (e.g. PDA) that can be used in the physical museum space. To connect users' various interactions with these tools, we made a conversion of the online user model stored in RDF into XML format which the mobile guide can parse, and in this way we keep the online and on-site user models dynamically synchronized. Chapter 4 presents the second generation of the Mobile Tour Guide with a real time routing system on different mobile devices (e.g. iPod). Compared with the first generation, it can adapt museum tours based on the user's ratings artworks and concepts, her/his current location in the physical museum and the coordinates of the artworks and rooms in the museum. In addition, we mapped the CHIP user model to an existing event model ontology SEM. Besides ratings, it can store additional user activities, such as following a tour and viewing artworks. Chapter 5 identifies a number of semantic relations within one vocabulary (e.g. a concept has a broader/narrower concept) and across multiple vocabularies (e.g. an artist is associated to an art style). We applied all these relations as well as the basic artwork features in content-based recommendations and compared all of them in terms of usefulness. This investigation also enables us to look at the combined use of artwork features and semantic relations in sequence and derive user navigation patterns. Chapter 6 defines the task of personalized recommendations and decomposes the task into a number of inference steps for ontology-based recommender systems, from a perspective of knowledge engineering. We proposed a hybrid approach combining both explicit and implicit recommendations. The explicit relations include artworks features and semantic relations with preliminary weights which are derived from the evaluation in Chapter 5. The implicit relations are built between art concepts based on instance-based ontology matching. Chapter 7 gives an example of reusing user interaction data generated by one application into another one for providing cross-application recommendations. In this example, user tagging about cultural events, gathered by iCITY, is used to enrich the user model for generating content-based recommendations in the CHIP Art Recommender. To realize full tagging interoperability, we investigated the problems that arise in mapping user tags to domain ontologies, and proposed additional mechanisms, such as the use of SKOS matching operators to deal with the possible mis-alignment of tags and domain-specific ontologies. We summarized to what extent the problem statement and each of the research questions are answered in Chapter 8. We also discussed a number of limitations in our research and looked ahead at what may follow as future work

Shared visiting in Equator city

In this paper we describe an infrastructure and prototype system for sharing of visiting experiences across multiple media. The prototype supports synchronous co-visiting by physical and digital visitors, with digital access via either the World Wide Web or 3-dimensional graphics

Visualization for Recommendation Explainability: A Survey and New Perspectives

Providing system-generated explanations for recommendations represents an important step towards transparent and trustworthy recommender systems. Explainable recommender systems provide a human-understandable rationale for their outputs. Over the last two decades, explainable recommendation has attracted much attention in the recommender systems research community. This paper aims to provide a comprehensive review of research efforts on visual explanation in recommender systems. More concretely, we systematically review the literature on explanations in recommender systems based on four dimensions, namely explanation goal, explanation scope, explanation style, and explanation format. Recognizing the importance of visualization, we approach the recommender system literature from the angle of explanatory visualizations, that is using visualizations as a display style of explanation. As a result, we derive a set of guidelines that might be constructive for designing explanatory visualizations in recommender systems and identify perspectives for future work in this field. The aim of this review is to help recommendation researchers and practitioners better understand the potential of visually explainable recommendation research and to support them in the systematic design of visual explanations in current and future recommender systems.Comment: Updated version Nov. 2023, 36 page

Social software for music

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

Design of an E-learning system using semantic information and cloud computing technologies

Humanity is currently suffering from many difficult problems that threaten the life and survival of the human race. It is very easy for all mankind to be affected, directly or indirectly, by these problems. Education is a key solution for most of them. In our thesis we tried to make use of current technologies to enhance and ease the learning process. We have designed an e-learning system based on semantic information and cloud computing, in addition to many other technologies that contribute to improving the educational process and raising the level of students. The design was built after much research on useful technology, its types, and examples of actual systems that were previously discussed by other researchers. In addition to the proposed design, an algorithm was implemented to identify topics found in large textual educational resources. It was tested and proved to be efficient against other methods. The algorithm has the ability of extracting the main topics from textual learning resources, linking related resources and generating interactive dynamic knowledge graphs. This algorithm accurately and efficiently accomplishes those tasks even for bigger books. We used Wikipedia Miner, TextRank, and Gensim within our algorithm. Our algorithm‘s accuracy was evaluated against Gensim, largely improving its accuracy. Augmenting the system design with the implemented algorithm will produce many useful services for improving the learning process such as: identifying main topics of big textual learning resources automatically and connecting them to other well defined concepts from Wikipedia, enriching current learning resources with semantic information from external sources, providing student with browsable dynamic interactive knowledge graphs, and making use of learning groups to encourage students to share their learning experiences and feedback with other learners.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Luis Sánchez Fernández.- Secretario: Luis de la Fuente Valentín.- Vocal: Norberto Fernández Garcí