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Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
ISBN: 978-1-4244-5445-7
pp: 381-384
Bo Zhao , Department of Computer Science, University of Illinois at Urbana-Champaign, USA
Bolin Ding , Department of Computer Science, University of Illinois at Urbana-Champaign, USA
Jiawei Han , Department of Computer Science, University of Illinois at Urbana-Champaign, USA
Chengxiang Zhai , Department of Computer Science, University of Illinois at Urbana-Champaign, USA
ABSTRACT
Previous studies on supporting keyword queries in RDBMSs provide users with a ranked list of relevant linked structures (e.g. joined tuples) or individual tuples. In this paper, we aim to support keyword search in a data cube with text-rich dimension(s) (so-called text cube). Each document is associated with structural dimensions. A cell in the text cube aggregates a set of documents with matching dimension values on a subset of dimensions. Given a keyword query, our goal is to find the top-k most relevant cells in the text cube. We propose a relevance scoring model and efficient ranking algorithms. Experiments are conducted to verify their efficiency.
CITATION
Bo Zhao, Bolin Ding, Jiawei Han, Chengxiang Zhai, "TopCells: Keyword-based search of top-k aggregated documents in text cube", ICDE, 2010, 2013 IEEE 29th International Conference on Data Engineering (ICDE), 2013 IEEE 29th International Conference on Data Engineering (ICDE) 2010, pp. 381-384, doi:10.1109/ICDE.2010.5447838
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