This paper presents DEDALE, a spatial database system intended to overcome some limitations of current systems by providing an abstract and non-specialized data model query language for the representation manipulation objects. DEDALE relies on logical based linear constraints, which generalizes constraint [KKR90]. While in classical model, is always decomposed into its convex components, holes are allowed fit need practical applications. The although slightly more costly memory, has...

We propose a scalable distributed data structure (SDDS) called SD-Rtree. intend our for point and window queries over possibly large spatial datasets on clusters of interconnected servers. SD-Rtree generalizes the well-known Rtree structure. It uses balanced binary tree that scales with insertions to potentially any number storage servers through splits overloaded ones. A user/application manipulates from client node. The addresses its image can make outdated. This may generate addressing...

Article Free Access Share on Spatio-temporal data handling with constraints Authors: Stéphane Grumbach LASI and INRIA, Le Chesnay, France FranceView Profile , Philippe Rigaux CEDRIC/CNAM, Paris, Luc Segoufin Authors Info & Claims GIS '98: Proceedings of the 6th ACM international symposium Advances in geographic information systemsNovember 1998 Pages 106–111https://doi.org/10.1145/288692.288712Online:01 November 1998Publication History 33citation406DownloadsMetricsTotal Citations33Total...

Given a large set of items and users, we consider the problem collecting user preferences - or ratings on items. The paper describes simple method which provides an approximate solution to without requiring each rate item. relies iterative process. Each step, ballot, requires sample A collaborative filtering algorithm is then performed predict missing as well their level confidence (which initially 0). Perfoming new ballot allows improve accuracy predictions. administrator system responsible...

MapReduce has become an attractive and dominant model for processing large-scale datasets. However, this is not designed to directly support operations with multiple inputs as joins. Many studies on join algorithms including Bloom in have been conducted but they still too much non-joining data generated transmitted over the network. This research will help us eliminate problem by providing intersection filter based probabilistic models remove most disjoint elements between two Namely, three...

Many applications rely on sequence databases and use extensively pattern-matching queries to retrieve data of interest. This paper extends the traditional expressions parameterized patterns, featuring variables. Parameterized patterns are more expressive allow define concisely regular that would be very complex describe without They can also used express additional constraints patterns' variables.We show they evaluated cost with respect techniques (e.g., Knuth-Morris-Pratt algorithm). We an...

In this paper we propose a classification model formoving objects trajectories.We assume that the classificationis based on multi-scale map, and simplydefine trajectory pattern as sequence of zones anobject crosses during its travel.These patterns constitutethe basis operators.We also definea pattern-based query language which allows an onlineand continuous moving objects.Finallya prototype shows validity approach isbriefly described.