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García-Molina, Héctor; Papakonstantinou, Yannis; Quass, Dallan; Rajaraman, Anand; Sagiv, Yehoshua; Ullman, Jeffrey D.; Vassalos, Vasilis; Widom, Jennifer

doi:10.1023/a:1008683107812

Cited by 551 publications

(37 citation statements)

References 20 publications

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“…Most versions of datalog implement safety using syntactic checks proposed by Ullman (e.g. all head variables must occur in the rule body, and any variables in an arithmetic or relational subgoal must also appear in a positive relational subgoal) [9]. While efficient to implement, these safety rules are in fact too strong (e.g.…”

Section: Resultsmentioning

confidence: 99%

Mapping ORM to Datalog: An Overview

Halpin

Curland²,

Stirewalt³

et al. 2010

On the Move to Meaningful Internet Systems: OTM 2010 Workshops

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Abstract:Optimization of modern businesses is becoming increasingly dependent on business intelligence and rule-based software to perform predictive analytics over massive data sets and enforce complex business rules. This has led to a resurgence of interest in datalog, because of its powerful capability for processing complex rules, especially those involving recursion, and the exploitation of novel data structures that provide performance advantages over relational database systems. ORM 2 is a conceptual approach for fact oriented modeling that provides a high level graphical and textual syntax to facilitate validation of data models and complex rules with nontechnical domain experts. Datalog LB is an extended form of typed datalog that exploits fact-oriented data structures to provide deep and highly performant support for complex rules with guaranteed decidability. This paper provides an overview of recent research and development efforts to extend the Natural ORM Architect (NORMA) software tool to map ORM models to Datalog LB .

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Section: Resultsmentioning

confidence: 99%

Mapping ORM to Datalog: An Overview

Halpin

Curland²,

Stirewalt³

et al. 2010

On the Move to Meaningful Internet Systems: OTM 2010 Workshops

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show abstract

“…PIST [9] (2008) (Space grid + B-tree) Divide space into grids, and every cell build a time index. QuadTree [10] (2010) (Quadtree + time index) Build an unbalanced quad tree based on overload, every sub-region covered by a quad tree leaf node builds a time index.…”

Section: Related Workmentioning

confidence: 99%

“…Existing space division indexes are mainly nested indexes [10], which index the time dimension and spatial dimensions consequently. In other words, nested indexes do not consider temporal and spatial factors simultaneously.…”

Section: Motivation Of Attimentioning

confidence: 99%

ATTI: Workload-Aware Query Adaptive OcTree Based Trajectory Index

Meng

Wang

Lin

2013

IEICE Trans. Inf. & Syst.

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SUMMARYThe GPS trajectory databases serve as bases for many intelligent applications that need to extract some trajectories for future processing or mining. When doing such tasks, spatio-temporal range queries based methods, which find all sub-trajectories within the given spatial extent and time interval, are commonly used. However, the history trajectory indexes of such methods suffer from two problems. First, temporal and spatial factors are not considered simutaneously, resulting in low performance when processing spatio-temporal queries. Second, the efficiency of indexes is sensitive to query size. The query performance changes dramatically as the query size changed. This paper proposes workload-aware Adaptive OcTree based Trajectory clustering Index (ATTI) aiming at optimizing trajectory storage and index performance. The contributions are three-folds. First, the distribution and time delay of the trajectory storage are introduced into the cost model of spatio-temporal range query; Second, the distribution of spatial division is dynamically adjusted based on GPS update workload; Third, the query workload adaptive mechanism is proposed based on virtual OcTree forest. A wide range of experiments are carried out over Microsoft GeoLife project dataset, and the results show that query delay of ATTI could be about 50% shorter than that of the nested index.

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“…This article addresses the query rewriting problem in semantic data integration in a very general form, as a proper generalization of the wellknown local-as-view (e.g., [20,12,3]) and global-asview approaches (e.g., [11,2,6]). …”

Section: Introductionmentioning

confidence: 99%

Query Rewriting with Symmetric Constraints

Koch

2002

Lecture Notes in Computer Science

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We address the problem of answering queries using expressive symmetric inter-schema constraints which allow to establish mappings between several heterogeneous information systems. This problem is of high relevance to data integration, as symmetric constraints are essential for dealing with true concept mismatch and are generalizations of the kinds of mappings supported by both local-as-view and global-as-view approaches that were previously studied in the literature. Moreover, the flexibility gained by using such constraints for data integration is essential for virtual enterprise and e-commerce applications. We first discuss resolution-based methods for computing maximally contained rewritings and characterize computability aspects. Then we propose an alternative but semantically equivalent perspective based on a generalization of results relating to the database-theoretic problem of answering queries using views. This leads to a fast query rewriting algorithm based on AI techniques, which has been implemented and experimentally evaluated.

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Untitled

Cited by 551 publications

References 20 publications

Mapping ORM to Datalog: An Overview

Mapping ORM to Datalog: An Overview

ATTI: Workload-Aware Query Adaptive OcTree Based Trajectory Index

Query Rewriting with Symmetric Constraints

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