Indexing Uncertain Categorical Data over Distributed Environment

DOI

10.2991/ifsa-eusflat-15.2015.197How to use a DOI?

Keywords

Uncertain database, indexating, distributed environment, top-k query, query optimization, threshold query.

Abstract

Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases incuding indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for effciently searching uncertain categorical data over distributed environments. We adress two kinds of query over the distributed uncertain databases, one a distributed probabilistic thresholds query, where all results sastisfying the query with probablities that meet a probablistic threshold requirement are returned, and another a distributed top k-queries, where all results optimizing the transfer of the tuples and the time reatment are returned.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Adel Benaissa
AU  - Salima Benbernou
AU  - Mourad Ouziri
AU  - Soror Sahri
PY  - 2015/06
DA  - 2015/06
TI  - Indexing Uncertain Categorical Data over Distributed Environment
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 1395
EP  - 1400
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.197
DO  - 10.2991/ifsa-eusflat-15.2015.197
ID  - Benaissa2015/06
ER  -