SPOT Databases: Efficient Consistency Checking and Optimistic Selection in Probabilistic Spatial Databases

Parker, Austin; Infantes, Guillaume; Grant, John; Subrahmanian, V. S.

doi:10.1109/tkde.2008.93

Cited by 11 publications

(11 citation statements)

References 27 publications

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“…The problem of querying SPOT data has been investigated by Parker et al (2007aParker et al ( , 2009), Parisi, Parker, Grant, and Subrahmanian (2010), and Grant, Molinaro, and Parisi (2013) in more specific frameworks corresponding to PST KBs (of the form A, ∅ ), where only PST atoms were considered. In this section, we address the problem of answering selection queries in general (consistent) PST KBs.…”

Section: Optimistic and Cautious Answersmentioning

confidence: 99%

“…In this section, we address the problem of answering selection queries in general (consistent) PST KBs. These kinds of queries were considered by Parker et al (2007aParker et al ( , 2009 A selection query is an expression of the form (?id, q, ?t, [ , u]), where q is a region and [ , u] is a probability interval. Intuitively, a selection query says: "Given a region q and a probability interval [ , u], find all objects id and times t such that id is inside q at time t with a probability in the interval [ , u]."…”

Section: Optimistic and Cautious Answersmentioning

confidence: 99%

“…The problem of deciding whether a pair id, t is an optimistic/cautious answer to a selection query Q can be solved in polynomial time for PST KBs whose F component is empty (Parker et al, 2007a(Parker et al, , 2009Parisi et al, 2010). However, in the presence of integrity constraints this problem becomes hard.…”

Section: Complexity Of Query Answeringmentioning

confidence: 99%

“…Past work on the SPOT framework investigated efficient algorithms for computing optimistic and cautious answers to selection queries (Parker et al, 2009;Parisi et al, 2010). The initial SPOT framework on which we build by adding integrity constraints has been implemented and tested on real US Navy databases containing ship location data (Parker et al, 2009;Parisi et al, 2010).…”

Section: Spatio-temporal Approachesmentioning

confidence: 99%

“…The initial SPOT framework on which we build by adding integrity constraints has been implemented and tested on real US Navy databases containing ship location data (Parker et al, 2009;Parisi et al, 2010). Aggregate queries have been recently investigated by , who proposed three semantics along with computational methods for evaluating them.…”

Section: Spatio-temporal Approachesmentioning

confidence: 99%

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Knowledge Representation in Probabilistic Spatio-Temporal Knowledge Bases

Parisi¹,

Grant²

2016

jair

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We represent knowledge as integrity constraints in a formalization of probabilistic spatiotemporal knowledge bases. We start by defining the syntax and semantics of a formalization called PST knowledge bases. This definition generalizes an earlier version, called SPOT, which is a declarative framework for the representation and processing of probabilistic spatio-temporal data where probability is represented as an interval because the exact value is unknown. We augment the previous definition by adding a type of non-atomic formula that expresses integrity constraints. The result is a highly expressive formalism for knowledge representation dealing with probabilistic spatio-temporal data. We obtain complexity results both for checking the consistency of PST knowledge bases and for answering queries in PST knowledge bases, and also specify tractable cases. All the domains in the PST framework are finite, but we extend our results also to arbitrarily large finite domains.

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