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Evaluating Probabilistic Queries over Imprecise Data (2003)
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| Venue: | In SIGMOD |
| Citations: | 274 - 45 self |
BibTeX
@INPROCEEDINGS{Cheng03evaluatingprobabilistic,
author = {Reynold Cheng},
title = {Evaluating Probabilistic Queries over Imprecise Data},
booktitle = {In SIGMOD},
year = {2003},
pages = {551--562}
}
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Abstract
Sensors are often employed to monitor continuously changing entities like locations of moving ob-jects and temperature. The sensor readings are reported to a database system, and are subsequently used to answer queries. Due to continuous changes in these values and limited resources (e.g., net-work bandwidth and battery power), the database may not be able to keep track of the actual values of the entities. Queries that use these old values may produce incorrect answers. However, if the degree of uncertainty between the actual data value and the database value is limited, one can place more confidence in the answers to the queries. More generally, query answers can be augmented with probabilistic guarantees of the validity of the answers. In this paper, we study probabilistic query evaluation based on uncertain data. A classification of queries is made based upon the nature of the result set. For each class, we develop algorithms for computing probabilistic answers, and provide efficient indexing and numeric solutions. We address the important issue of measuring the quality of the answers to these queries, and provide algorithms for efficiently pulling data from relevant sensors or moving objects in order to improve the quality of the executing queries. Extensive experiments
Keyphrases
probabilistic query imprecise data query answer relevant sensor net-work bandwidth actual value database system extensive experiment probabilistic guarantee incorrect answer continuous change battery power actual data value probabilistic answer result set limited resource numeric solution sensor reading uncertain data important issue efficient indexing probabilistic query evaluation database value old value
