DATA AND KNOWLEDGE

ENGINEERING GROUP

Children are a fast growing user group on the Internet. Among different online activities, children use web search engines in order to gather information related to their personal interests and school activities. Children's knowledge, cognitive abilities and fine motor skills are different from those of adults. Therefore, they may experience difficulties with search engines that are built using standard information retrieval algorithms and search interfaces for adults. Special or targeted search engines for children are essential in order to better support children in their search tasks. However, the design of search solutions for children is not an easy task. Not only are children's abilities different from the abilities of adults, children also undergo relatively fast changes in their abilities. In order to tackle this challenge, an age-adaptable information terminal for children with a special focus on the search user interface (SUI) has been developed in three stages following a user-centered design. Specifically, it addresses the changing characteristics of the users by providing a means of adaptation. Several user studies have been conducted with children during the development to ensure the usability of the information terminal.

In this paper we present a conceptual framework for exploratory search by structuring web results based on concept lattices, which are created using methods from Formal Concept Analysis (FCA). The approach is to organize query based search engine results (web documents) by a hierarchy of clusters that are composed of documents with similar attributes. The resulting concept lattice provides a structured view on query-related domains and hence can improve the user's understanding of document attributes and shared features. Instead of using the traditional approaches, we applied a fuzzy extension of FCA in order to support the usage of different types of attributes within the analyzed result set. Afterward the result set is presented using the graph visualization toolkit CET.

Um Kinder bei der Informationssuche angemessen unterstützen zu können, muss ihr Entwicklungsstand – und die damit verbundenen speziellen Bedürfnisse und Fähigkeiten – beim Design von Informationssystemen berücksichtigt werden. Existierende Systeme sind meist speziell für die Zielgruppe erwachsener Nutzer konzipiert und berücksichtigen somit nicht die besonderen Bedürfnisse der stark wachsenden Gruppe junger Nutzer, die heutzutage immer früher mit Informationssystemen in Kontakt kommt. In diesem Artikel fassen wir die Ergebnisse aktueller Arbeiten und Studien im Bereich der Informationssuche von jungen Nutzern zusammen. Anschießend leiten wir Empfehlungen für die Gestaltung von kinderfreundlichen Informationssystemen, u. a. basierend auf eigenen Arbeiten, ab.

We describe an information terminal that supports interactive search with an age-adaptable search user interface whose main focus group are young users. The terminal enables a flexible adaptation of the search user interface to address changing requirements of users at different age groups. The interface is operated using touch interactions as they are considered to be more natural for children than using a mouse. Users search within a safe environment; For this purpose a search index was created using a focused crawler.

To date, children come more and more often into contact with information systems. Unfortunately, these systems are usually designed for adults and the increasing group of young users has been widely neglected. In order to create and support children's information seeking appropriately, we have to consider their specific state of development resulting into different needs and capabilities. In this paper, we discuss the design and the results of a user study to analyze exploratory voice-controlled search of young users. Exploratory search nicely reflects real-life information needs and voice-controlled interfaces have the advantage that children do not need to have good spelling skills. Hence the interaction can be more intuitive and motivating. We gained first insights into the children's search behavior in context of exploratory search and identified design issues for similar studies. Furthermore, we illustrate the challenges and potential benefits of interactive voice-controlled search systems for young users.

In order to provide a qualitative support to the users during a web search, it is important to have access to a multitude of information sources simultaneously. Depending on the available domain expertise, the user can get an overview and insight to different information perspectives and compare the quality of resources. In this work, we present an exploratory search engine that simultaneously accesses internet resources and a local knowledge base given in the form of ontologies. The ontologies are used to define the search context and can be extended during exploration with new information, thus making the search process adaptive and iterative. We demonstrate our system on an example from the fitness domain, where the user searches for physical training exercises on the Web to complete a personal training plan.

The development of systems to support collaborative information seeking is a challenging issue for many reasons. Besides the support expected for an individual user, such as query formulation, relevance judgement, result set organization and summarization, the smooth exchange of search related information within the team of users seeking information has to be supported. This imposes strong requirements on visualization and interaction to enable user to easily trace and interpret the search activities of other team members and to jointly make sense of gathered information in order to solve the initial information need. In this paper, we briefly motivate specific requirements with a focus on collaborative professional search, review existing work and point out major challenges. In addition, we briefly introduce a system that has been specifically developed to support collaborative technology search.

Many real-world networks have a structure of overlapping cohesive groups. In order to uncover this structure several clustering algorithms have been developed. In this paper, we focus on the evaluation of these algorithms. Quality measures are commonly used for this purpose and provide a means to assess the quality of a derived cluster structure. Currently, there are too few measures for graph clusterings with overlaps available that would enable a meaningful evaluation, even though many well studied crisp quality measures exist. In order to expand the pool of overlapping measures we propose three methods to adapt existing crisp quality measures so that they can handle graph overlaps appropriately. We demonstrate our methods on the well known measures Density, Modularity and Conductance. We also propose an enhancement of an existing modularity measure for networks with overlapping structure. We analyse the proposed quality indices using experiments on artificial graphs that possess overlapping structure. For this evaluation, we apply a graph generation model to create clustered graphs with overlaps that are similar to real-world networks, i.e., their node degree and cluster size distribution follow a power law.