Dual retrieval in conceptual information systems

Conceptual Information Systems provide a multi-dimensional conceptually structured view on data stored in relational databases. On restricting the expressiveness of the retrieval language, they allow the visualization of sets of realted queries in conceptual hierarchies, hence supporting the search of something one does not have a precise description, but only a vague idea of. Information Retrieval is considered as the process of finding specific objects (documents etc.) out of a large set of objects which fit to some description. In some data analysis and knowledge discovery applications, the dual task is of interest: The analyst needs to determine, for a subset of objects, a description for this subset. In this paper we discuss how Conceptual Information Systems can be extended to support also the second task.

Hierarchies of conceptual scales

Formal Concept Analysis allows to derive conceptual hierarchies from data tables. Formal Concept Analysis is applied in various domains, e.g., data analysis, information retrieval, and knowledge discovery in databases. In order to deal with increasing sizes of the data tables (and to allow more complex data structures than just binary attributes), conceputal scales habe been developed. They are considered as metadata which structure the data conceptually. But in large applications, the number of conceptual scales increases as well. Techniques are needed which support the navigation of the user also on this meta-level of conceptual scales. In this paper, we attack this problem by extending the set of scales by hierarchically ordered higher level scales and by introducing a visualization technique called nested scaling. We extend the two-level architecture of Formal Concept Analysis (the data table plus one level of conceptual scales) to many-level architecture with a cascading system of conceptual scales. The approach also allows to use representation techniques of Formal Concept Analysis for the visualization of thesauri and ontologies.

Interface issues in the ESCHER visual database editor

Presentation at the 1997 Dagstuhl Seminar "Evaluation of Multimedia Information Retrieval", Norbert Fuhr, Keith van Rijsbergen, Alan F. Smeaton (eds.), Dagstuhl Seminar Report 175, 14.04. - 18.04.97 (9716). - Abstract: This presentation will introduce ESCHER, a database editor which supports visualization in non-standard applications in engineering, science, tourism and the entertainment industry. It was originally based on the extended nested relational data model and is currently extended to include object-relational properties like inheritance, object types, integrity constraints and methods. It serves as a research platform into areas such as multimedia and visual information systems, QBE-like queries, computer-supported concurrent work (CSCW) and novel storage techniques. In its role as a Visual Information System, a database editor must support browsing and navigation. ESCHER provides this access to data by means of so called fingers. They generalize the cursor paradigm in graphical and text editors. On the graphical display, a finger is reflected by a colored area which corresponds to the object a finger is currently pointing at. In a table more than one finger may point to objects, one of which is the active finger and is used for navigating through the table. The talk will mostly concentrate on giving examples for this type of navigation and will discuss some of the architectural needs for fast object traversal and display. ESCHER is available as public domain software from our ftp site in Kassel. The portable C source can be easily compiled for any machine running UNIX and OSF/Motif, in particular our working environments IBM RS/6000 and Intel-based LINUX systems. A porting to Tcl/Tk is under way.

Bereitstellung von Früherkennungsinformationen für Unternehmen - Entwicklung und Einsatz eines Softwareinstrumentes

Die Unternehmensumwelt wird zunehmend von dynamischen Veränderungen und Turbulenzen geprägt. Globalisierung der Märkte und schneller wechselnde Umfeldveränderungen zwingen die Unternehmen dazu, ihr strategisches Verhalten ständig an neue Bedingungen anzupassen. Ein vorausschauendes Denken und Handeln wird immer notwendiger, da in vielen Branchen Produkte und Dienstleistungen in wesentlich kürzeren Zeitabständen als bisher durch Neue ersetzt werden. Um das unternehmerische Umfeld im Blick zu haben und über Pläne, Leistungen und Kompetenzen der Konkurrenten und Kunden über Marktveränderungen und technische Neuerungen etc. aktuell und vorausschauend informiert zu sein, wird ein intelligentes, systematisches Vorgehen bei der Informationsversorgung mit Umfeldinformationen benötigt. Die Dissertation befasst sich mit der Entwicklung, Implementierung und Untersuchung eines Softwareinstrumentes und systematischen Arbeitsprozesses, um die Versorgung von Managern und Mitarbeitern mit Umfeldinformationen (externen Informationen) zu verbessern um aufkommende Chancen und/oder Risiken frühzeitig zu erkennen. Der Schwerpunkt der Arbeit bezieht sich hauptsächlich auf die Phase der Informationsbereitstellung (Beschaffung, Verarbeitung und Präsentation) und dem Abruf der Umfeldinformationen durch die Manager und Mitarbeiter. Das entwickelte Softwareinstrument und die Arbeitsabläufe werden in drei Untersuchungsfirmen implementiert und evaluiert. Über eine schriftliche Befragung soll der Zustand vor Einführung des Softwareinstrumentes und Arbeitsabläufen und ein Jahr danach erfasst werden. Zur Ergänzung der Ergebnisse der schriftlichen Erhebung werden zusätzlich leitfadengestützte Einzelinterviews durchgeführt werden. Spezielle Auswertungen der Systemzugriffe sollen Aufschluss über den Nutzungsumfang und -häufigkeit im Zeitablauf geben. Über eine sukzessive Optimierung der Software und Arbeitsabläufe werden abschließend ein überarbeitetes Softwareinstrument sowie angepasste Arbeitsabläufe und ein Einführungsverfahren vorgestellt.

Network properties of folksonomies

Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of the systems. We consider their underlying data structures – socalled folksonomies – as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them. Subsequently, we introduce a network of tag co-occurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.

Network properties of folksonomies

Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of these systems. We consider their underlying data structures – so-called folksonomies – as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them. Subsequently, we introduce a network of tag cooccurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.

Identifying the factors governing attitude towards the e-Agriservice among dairy farmers in Maharashtra, India

Information and communication technology (ICT) projects have a great potential to revolutionise the information delivery system by bridging the gap between farmers and extension personnel. aAQUA (Almost All Questions Answered) portal was launched by the Developmental Informatics Laboratory (DIL) at Indian Institute of Technology (IIT) Mumbai, Maharashtra, India in 2003 as an information providing system to deliver technology options and tailored information for the problems and queries raised by Indian dairy farmers. To measure the effectiveness of this service the attitudinal dimensions of the users of aAQUA e-Agriservice were investigated using a 22 item scale. A simple random sampling technique was used to select 120 dairy farmers from which data were collected and subjected to factor analysis to identify the underlying constructs in this research. From the attitude items, four components were extracted and named as the pessimistic, utility, technical and efficacy perspective, which influenced the development of varied level of attitudinal inclination towards the e-Agriservice. These components explained 64.40 per cent of variation in the attitude of the users towards the aAQUA e-Agriservice. This study provides a framework for technically efficient service provision that might help to reduce the pessimistic attitude of target population to adopt e-Agriservice in their farming system. The results should also be helpful for researchers, academics, ICT based service providers and policy makers to consider these perspectives while planning and implementing ICT projects.