This article presents the semantic portal MUSEUMFINLAND for publishing heterogeneous museum collections on the Semantic Web. It is shown how museums with their semantically rich and interrelated collection content can create a large, consolidated semantic collection portal together on the web. By sharing a set of ontologies, it is possible to make collections semantically interoperable, and provide the museum visitors with intelligent content-based search and browsing services to the global collection base. The architecture underlying MUSEUMFINLAND separates generic search and browsing services from the underlying application dependent schemas and metadata by a layer of logical rules. As a result, the portal creation framework and software developed has been applied successfully to other domains as well. MUSEUMFINLAND got the Semantic Web Challence Award (second prize) in 2004.

This paper generalizes the idea of traditional syntactic text autocompletion onto the semantic level. The idea is to autocomplete typed text into ontological categories instead of words in a vocabulary. The idea has been implemented and its application for semantic indexing and content-based information retrieval in multi-facet search is proposed. Four operational semantic portals on the web using the implementation are presented as application cases. 1

Abstract—In common Web-based search interfaces, it can be difficult to formulate queries that simultaneously combine temporal, spatial, and topical data filters. We investigate how coordinated visualizations can enhance search and exploration of information on the World Wide Web by easing the formulation of these types of queries. Drawing from visual information seeking and exploratory search, we introduce VisGets – interactive query visualizations of Web-based information that operate with online information within a Web browser. VisGets provide the information seeker with visual overviews of Web resources and offer a way to visually filter the data. Our goal is to facilitate the construction of dynamic search queries that combine filters from more than one data dimension. We present a prototype information exploration system featuring three linked VisGets (temporal, spatial, and topical), and used it to visually explore news items from online RSS feeds. Index Terms—Information visualization, World Wide Web, information retrieval, exploratory search, visual information seeking. 1

This paper presents a case-study of converting the content of an existing eLearning portal based on the Learning Object Metadata (LOM) format into a semantic portal. It is shown how the content can be provided for the end-user from different semantic perspectives (views) based on a set of ontologies whose concepts are extracted from the original metadata. A semantic recommender system based on the same ontologies and metadata enhances the system usability further. This recommender system links the learning objects of the portal with each other with short labels that explain to the end-user the reason for the links, which is especially important in the eLearning domain. Furthermore, the system links the material also with the content of another cultural semantic portal, providing interportal semantic links. The application, consisting of some 2200 video and audio clips as learning objects, is available on the web where it can be compared with the original portal.

We show how the benefits of the view-based search method, developed within the information retrieval community, can be combined and extended with the benefits of ontology-based annotations and search, developed within the Semantic Web community. As a proof of the concept, we have implemented an ontology- and view-based image retrieval and recommendation browser Ontogator. Ontogator is innovative in two ways. Firstly, the RDFS-based ontologies used for annotating image metadata are used in the end user interface to facilitate viewbased image retrieval. The views provide the user with a search function and means for getting useful overviews of the contents in the repository. Secondly, a semantic browsing function is provided by a recommender system. This system enriches instance level image metadata by the ontology and provides the user with links to semantically related relevant images. The notion of a “semantically relevant link ” is specified in terms of logical rules. To illustrate and discuss the ideas, a practical application of Ontogator to a photo repository of the Helsinki University Museum is presented.

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Abstract. We show how the benefits of the view-based search method, developed within the information retrieval community, can be combined and extended with the benefits of ontology-based annotations and search, developed within the Semantic Web community. As a proof of the concept, we have implemented an ontology- and view-based image retrieval and recommendation browser Ontogator. Ontogator is innovative in two ways. Firstly, the RDFS-based ontologies used for annotating image metadata are used in the end user interface to facilitate viewbased image retrieval. The views provide the user with a search function and means for getting useful overviews of the contents in the repository. Secondly, a semantic browsing function is provided by a recommender system. This system enriches instance level image metadata by the ontology and provides the user with links to semantically related relevant images. The notion of a “semantically relevant link ” is specified in terms of logical rules. To illustrate and discuss the ideas, a practical application of Ontogator to a photo repository of the Helsinki University Museum is presented. 1

We introduce the information flaneur as a new human-centred view on information seeking that is grounded in interdisciplinary research. We use the metaphor of the urban flaneur making sense of a city as an inspiring lens that brings together diverse perspectives. These perspectives shift information seeking towards a more optimistic outlook: the information flaneur represents curious, creative, and critical information seeking. The resulting information-seeking model conceptualizes the interrelated nature between information activities and experiences as a continuum between horizontal exploration and vertical immersion. Motivated by enabling technological trends and inspired by the information flaneur, we present explorability as a new guiding principle for design and raise research challenges regarding the representation of information abstractions and details.

Data mining is typically applied to large databases of highly structured information in order to discover new knowledge. In businesses and institutions, the amount of information existing in repositories of text documents usually rivals or surpasses the amount found in relational databases. Though the amount of potentially valuable knowledge contained in document collections can be great, they are often difficult to analyze. Therefore, it is important to develop methods to efficiently discover knowledge embedded in these document repositories. In this paper we describe an approach for mining knowledge from text collections by applying data mining techniques to metadata records generated via automated text categorization. By controlling the set of metadata fields as well as the set of assigned categories we can customize the knowledge discovery task to address specific questions. As an example, we apply the approach to a large collection of product reviews and evaluate the performance of the knowledge discovery.

This thesis explores the possibilities of using the view-based search paradigm to create intelligent search interfaces on the Semantic Web. After surveying several current seman-tic search techniques, the view-based search paradigm is explained, and argued to fit in a valuable niche in the field. To test the argument, OntoViews, a semantic view-based search portal creation tool was designed and implemented, and eight portals with five vastly dif-ferent user interfaces were built using it. Based on the results of these experiments, this thesis argues that the paradigm, particularly as implemented in the OntoViews tool pro-vides a strong, extensible and flexible base on which to built semantic search applications. The particular problems faced in applying view-based search for semantic interfaces are noted, along with explanations on how they were solved in the OntoViews architecture. Finally, directions and ideas for future research are presented for both the paradigm and the implementation architecture, respectively.