Probabilistic Range Querying over Gaussian Objects

• DONG Tingting

  Graduate School of Information Science, Nagoya University

• XIAO Chuan

  Graduate School of Information Science, Nagoya University

• ISHIKAWA Yoshiharu

  Graduate School of Information Science, Nagoya University

Abstract

Probabilistic range query is an important type of query in the area of uncertain data management. A probabilistic range query returns all the data objects within a specific range from the query object with a probability no less than a given threshold. In this paper, we assume that each uncertain object stored in the database is associated with a multi-dimensional Gaussian distribution, which describes the probability distribution that the object appears in the multi-dimensional space. A query object is either a certain object or an uncertain object modeled by a Gaussian distribution. We propose several filtering techniques and an R-tree-based index to efficiently support probabilistic range queries over Gaussian objects. Extensive experiments on real data demonstrate the efficiency of our proposed approach.

Journal

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E97.D (4), 694-704, 2014

  The Institute of Electronics, Information and Communication Engineers

Keywords

• uncertain data
• probabilistic databases
• Gaussian distribution
• range queries

Details

• CRID: 1390001204377718784
• NII Article ID: 130003394894
• DOI: 10.1587/transinf.e97.d.694
• ISSN: 17451361
• ISSN: 09168532
• Web Site: https://www.jstage.jst.go.jp/article/transinf/E97.D/4/E97.D_694/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed