4,462 research outputs found

    Using Visualization to Support Data Mining of Large Existing Databases

    Get PDF
    In this paper. we present ideas how visualization technology can be used to improve the difficult process of querying very large databases. With our VisDB system, we try to provide visual support not only for the query specification process. but also for evaluating query results and. thereafter, refining the query accordingly. The main idea of our system is to represent as many data items as possible by the pixels of the display device. By arranging and coloring the pixels according to the relevance for the query, the user gets a visual impression of the resulting data set and of its relevance for the query. Using an interactive query interface, the user may change the query dynamically and receives immediate feedback by the visual representation of the resulting data set. By using multiple windows for different parts of the query, the user gets visual feedback for each part of the query and, therefore, may easier understand the overall result. To support complex queries, we introduce the notion of approximate joins which allow the user to find data items that only approximately fulfill join conditions. We also present ideas how our technique may be extended to support the interoperation of heterogeneous databases. Finally, we discuss the performance problems that are caused by interfacing to existing database systems and present ideas to solve these problems by using data structures supporting a multidimensional search of the database

    Info Navigator: A visualization tool for document searching and browsing

    Get PDF
    In this paper we investigate the retrieval performance of monophonic and polyphonic queries made on a polyphonic music database. We extend the n-gram approach for full-music indexing of monophonic music data to polyphonic music using both rhythm and pitch information. We define an experimental framework for a comparative and fault-tolerance study of various n-gramming strategies and encoding levels. For monophonic queries, we focus in particular on query-by-humming systems, and for polyphonic queries on query-by-example. Error models addressed in several studies are surveyed for the fault-tolerance study. Our experiments show that different n-gramming strategies and encoding precision differ widely in their effectiveness. We present the results of our study on a collection of 6366 polyphonic MIDI-encoded music pieces

    Supporting Data mining of large databases by visual feedback queries

    Get PDF
    In this paper, we describe a query system that provides visual relevance feedback in querying large databases. Our goal is to support the process of data mining by representing as many data items as possible on the display. By arranging and coloring the data items as pixels according to their relevance for the query, the user gets a visual impression of the resulting data set. Using an interactive query interface, the user may change the query dynamically and receives immediate feedback by the visual representation of the resulting data set. Furthermore, by using multiple windows for different parts of a complex query, the user gets visual feedback for each part of the query and, therefore, may easier understand the overall result. Our system allows to represent the largest amount of data that can be visualized on current display technology, provides valuable feedback in querying the database, and allows the user to find results which, otherwise, would remain hidden in the database

    Image mining: trends and developments

    Get PDF
    [Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

    CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

    Get PDF
    After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

    Identification of Design Principles

    Get PDF
    This report identifies those design principles for a (possibly new) query and transformation language for the Web supporting inference that are considered essential. Based upon these design principles an initial strawman is selected. Scenarios for querying the Semantic Web illustrate the design principles and their reflection in the initial strawman, i.e., a first draft of the query language to be designed and implemented by the REWERSE working group I4
    • 

    corecore