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DataLens: Making a Good First Impression

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    Publication properties
    Title: DataLens: Making a Good First Impression
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    Date: 2009
    Publication type: Conference paper
    Authors:
    No. First name Last name Show
    1. Bin Liu
    2. H.V. Jagadish
    Download (by DOI): 10.1145/1559845.1559997
    BibTeX: conf/sigmod/LiuJ09
    DBLP: db/conf/sigmod/sigmod2009.html#LiuJ09
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    Conference Track
    Conference Name: ACM SIGMOD International Conference on Management of Data, SIGMOD 2009, Providence, Rhode Island, USA, June 29 - July 2, 2009 2009
    Track Name: Demo
    URL: http://www.sigmod09.org/

    Abstract

    When a database query has a large number of results, the user can only be shown one page of results at a time. One popular approach is to rank results such that the "best" results appear first. This approach is well-suited for information retrieval, and for some database queries, such as similarity queries or under-specified (or keyword) queries with known (or guessable) user preferences. However, standard database query results comprise a set of tuples, with no associated ranking. It is typical to allow users the ability to sort results on selected attributes, but no actual ranking is defined.

    An alternative approach is not to try to show the estimated best results on the first page, but instead to help users learn what is available in the whole result set and direct them to finding what they need. We present DataLens, a framework that: i) generates the most representative data points to display on the first page without sorting or ranking, ii) allows users to drill-down to more similar items in a hierarchical fashion, and iii) dynamically adjusts the representatives based on the user's new query conditions. To the best of our knowledge, DataLens is the first to allow hierarchical database result browsing and searching at the same time.