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Wolfgang Gatterbauer

  1. Rules of Thumb for Information Acquisition from Large and Redundant Data.

    Пт, 12/17/2010 - 16:01 — SomNambul
    Authors: Wolfgang Gatterbauer
    Subjects: Information Retrieval
    Abstract

    We develop an abstract model of information acquisition from redundant data.
    We assume a random sampling process from data which provide information with
    bias and are interested in the fraction of information we expect to learn as
    function of (i) the sampled fraction (recall) and (ii) varying bias of
    information (redundancy distributions). We develop two rules of thumb with
    varying robustness.

  2. The Complexity of Causality and Responsibility for Query Answers and non-Answers.

    Пнд, 09/13/2010 - 15:01 — SomNambul
    Authors: Wolfgang Gatterbauer, Dan Suciu, Alexandra Meliou, Katherine M. Moore
    Subjects: Databases
    Abstract

    An answer to a query has a well-defined lineage expression (alternatively
    called how-provenance) that explains how the answer was derived. Recent work
    has also shown how to compute the lineage of a non-answer to a query. However,
    the cause of an answer or non-answer is a more subtle notion and consists, in
    general, of only a fragment of the lineage. In this paper, we adapt Halpern,
    Pearl, and Chockler's recent definitions of causality and responsibility to
    define the causes of answers and non-answers to queries, and their degree of
    responsibility.

  3. A Case for A Collaborative Query Management System.

    Чт, 09/10/2009 - 10:12 — SomNambul
    Authors: Nodira Khoussainova, Magda Balazinska, Wolfgang Gatterbauer, YongChul Kwon, Dan Suciu
    Subjects: Databases
    Abstract

    Over the past 40 years, database management systems (DBMSs) have evolved to
    provide a sophisticated variety of data management capabilities. At the same
    time, tools for managing queries over the data have remained relatively
    primitive. One reason for this is that queries are typically issued through
    applications. They are thus debugged once and re-used repeatedly. This mode of
    interaction, however, is changing. As scientists (and others) store and share
    increasingly large volumes of data in data centers, they need the ability to
    analyze the data by issuing exploratory queries.

Math-arch

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