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23
Complex spatio-temporal pattern queries
- In VLDB
, 2005
"... This paper introduces a novel type of query, what we name Spatio-temporal Pattern Queries (STP). Such a query specifies a spatio-temporal pattern as a sequence of distinct spatial predicates where the predicate temporal ordering (exact or relative) matters. STP queries can use various types of spati ..."
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Cited by 35 (4 self)
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This paper introduces a novel type of query, what we name Spatio-temporal Pattern Queries (STP). Such a query specifies a spatio-temporal pattern as a sequence of distinct spatial predicates where the predicate temporal ordering (exact or relative) matters. STP queries can use various types of spatial predicates (range search, nearest neighbor, etc.) where each such predicate is associated (1) with an exact temporal constraint (a time-instant or a time-interval), or (2) more generally, with a relative order among the other query predicates. Using traditional spatio-temporal index structures for these types of queries would be either inefficient or not an applicable solution. Alternatively, we propose specialized query evaluation algorithms for STP queries With Time. We also present a novel index structure, suitable for STP queries With Order. Finally, we conduct a comprehensive experimental evaluation to show the merits of our techniques. 1
A critical evaluation of location based services and their potential
- JOURNAL OF LOCATION BASED SERVICES EDITORIAL LEAD PAPER
"... This Editorial lead paper for the Journal of Location Based Services surveys this complex and multi-disciplinary field and identifies the key research issues. Although this field has produced early commercial disappointments, the inevitability that pervasive location-aware services on mobile devices ..."
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Cited by 16 (0 self)
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This Editorial lead paper for the Journal of Location Based Services surveys this complex and multi-disciplinary field and identifies the key research issues. Although this field has produced early commercial disappointments, the inevitability that pervasive location-aware services on mobile devices will emerge means that much research is needed to inform these developments. The paper reviews firstly: the science and technology of positioning, geographic information science, mobile cartography, spatial cognition and interfaces, information science, ubiquitous computing; and secondly the business, content and legal, social and ethics aspects, before synthesising the key issues for this new field.
Reporting Leaders and Followers Among Trajectories of Moving Point Objects
"... Abstract. Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio- ..."
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Cited by 16 (5 self)
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Abstract. Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern ‘one object is leading others’, which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.
Mixed-drove spatio-temporal co-occurrence pattern mining: A summary of results
- In ICDM
, 2006
"... Mixed-drove spatio-temporal co-occurrence patterns (MDCOPs) represent subsets of object-types that are located together in space and time. Discovering MDCOPs is an important problem with many applications such as identifying tactics in battlefields, games, and predator-prey interactions. However, mi ..."
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Cited by 14 (7 self)
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Mixed-drove spatio-temporal co-occurrence patterns (MDCOPs) represent subsets of object-types that are located together in space and time. Discovering MDCOPs is an important problem with many applications such as identifying tactics in battlefields, games, and predator-prey interactions. However, mining MDCOPs is computationally very expensive because the interest measures are computationally complex, datasets are larger due to the archival history, and the set of candidate patterns is exponential in the number of object-types. We propose a monotonic composite interest measure for discovering MDCOPs and a novel MDCOP mining algorithm. Analytical and experimental results show that the proposed algorithm is correct and complete. Results also show the proposed method is computationally more efficient than naïve alternatives. 1.
A Hybrid Model and Computing Platform for Spatio-semantic Trajectories ⋆
"... Abstract. Spatio-temporal data management has progressed significantly towards efficient storage and indexing of mobility data. Typically such mobility data analytics is assumed to follow the model of a stream of (x,y,t) points, usually coming from GPS-enabled mobile devices. With large-scale adopti ..."
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Cited by 10 (3 self)
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Abstract. Spatio-temporal data management has progressed significantly towards efficient storage and indexing of mobility data. Typically such mobility data analytics is assumed to follow the model of a stream of (x,y,t) points, usually coming from GPS-enabled mobile devices. With large-scale adoption of GPS-driven systems in several application sectors (shipment tracking to geo-social networks), there is a growing demand from applications to understand the spatio-semantic behavior of mobile entities. Spatio-semantic behavior essentially means a semantic (and preferably contextual) abstraction of raw spatio-temporal location feeds. The core contribution of this paper lies in presenting a Hybrid Model and a Computing Platform for developing a semantic overlay- analyzing and transforming raw mobility data (GPS) to meaningful semantic abstractions, starting from raw feeds to semantic trajectories. Secondly, we analyze large-scale GPS data using our computing platform and present results of extracted spatio-semantic trajectories. This impacts a large class of mobile applications requiring such semantic abstractions over streaming location feeds in real systems today. 1
Towards Semantic Trajectory Knowledge Discovery
"... Abstract. Trajectory data play a fundamental role to an increasing number of applications, such as transportation management, urban planning and tourism. Trajectory data are normally available as sample points. However, for many applications, meaningful patterns cannot be extracted from sample point ..."
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Abstract. Trajectory data play a fundamental role to an increasing number of applications, such as transportation management, urban planning and tourism. Trajectory data are normally available as sample points. However, for many applications, meaningful patterns cannot be extracted from sample points without considering the background geographic information. In this paper we propose a novel framework for semantic trajectory knowledge discovery. We propose to integrate trajectory sample points to the geographic information which is relevant to the application. Therefore, we extract the most important parts of trajectories, which are stops and moves, before applying data mining methods. Empirically we show the application and usability of our approach. 1.
Towards Semantic Trajectory Data Analysis: A Conceptual and Computational Approach ∗
"... Thanks to the rapid development of GPS mobile and wireless sensing technologies, the large-scale capture of evolving positioning data (so called trajectories) generated by moving objects has become technically and economically realistic. The data world becomes full of trajectories. The state-of-the- ..."
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Cited by 6 (0 self)
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Thanks to the rapid development of GPS mobile and wireless sensing technologies, the large-scale capture of evolving positioning data (so called trajectories) generated by moving objects has become technically and economically realistic. The data world becomes full of trajectories. The state-of-the-art on trajectory, either from the moving object database community or from the statistical analysis viewpoint, has built some sophisticated techniques for trajectory data modelling, storing, indexing, querying and mining. However, most of these existing methods mainly focus on the spatio-temporal features of trajectories; but the high-level semantic features of trajectory data are still in a less-explored area. Addressing this area, this doctoral work aims at bringing semantic concepts and statistical computations together for trajectory data analysis. We call this a “conceptual and computational ” approach, which involves three major perspectives, i.e. trajectory modelling, trajectory computing, and trajectory pattern discovery. 1.
Efficient Constraint Evaluation in Categorical Sequential Pattern Mining for Trajectory Databases
- In EDBT. 541–552
, 2009
"... The classic Generalized Sequential Patterns (GSP) algorithm re-turns all frequent sequences present in a database. However, usu-ally a few ones are interesting from a user’s point of view. Thus, post-processing tasks are required in order to discard uninterest-ing sequences. To avoid this drawback, ..."
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The classic Generalized Sequential Patterns (GSP) algorithm re-turns all frequent sequences present in a database. However, usu-ally a few ones are interesting from a user’s point of view. Thus, post-processing tasks are required in order to discard uninterest-ing sequences. To avoid this drawback, languages based on regular expressions (RE) were proposed to restrict frequent sequences to the ones that satisfy user-specified constraints. In all of these lan-guages, REs are applied over items, which limits their applicability in complex real-world situations. We propose a much powerful language, based on regular expressions, denoted RE-SPaM, where the basic elements are constraints defined over the (temporal and non-temporal) attributes of the items to be mined. Expressions in this language may include attributes, functions over attributes, and variables. We specify the syntax and semantics of RE-SPaM, and present a comprehensive set of examples to illustrate its expressive power. We study in detail how the expressions can be used to prune the resulting sequences in the mining process. In addition, we in-troduce techniques that allow pruning sequences in the early stages of the process, reducing the need to access the database, making use of the categorization of the attributes that compose the items, and of the automaton that accepts the language generated by the RE. Finally, we present experimental results. Although in this paper we focus on trajectory databases, our approach is general enough for being applied to other settings. 1.
A Query Language for Moving Object Trajectories
"... Trajectory properties are spatio-temporal properties that describe the changes of spatial (topological) relationships of one moving object with respect to regions and trajectories of other moving objects. Trajectory properties can be viewed as continuous changes of an object’s location resulting in ..."
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Cited by 3 (0 self)
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Trajectory properties are spatio-temporal properties that describe the changes of spatial (topological) relationships of one moving object with respect to regions and trajectories of other moving objects. Trajectory properties can be viewed as continuous changes of an object’s location resulting in a continuous change in the topological relationship between this object and other entities of interest. In this paper we develop a query language TQ for expressing trajectory properties. Our model and query language are based on the framework of constraint query languages. We present some preliminary complexity and expressive power results for the proposed language. 1
Aggregation Languages for Moving Object and Places of Interest Data
, 708
"... Abstract. We address aggregate queries over GIS data and moving object data, where non-spatial data are stored in a data warehouse. We propose a formal data model and query language to express complex aggregate queries. Next, we study the compression of trajectory data, produced by moving objects, u ..."
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Abstract. We address aggregate queries over GIS data and moving object data, where non-spatial data are stored in a data warehouse. We propose a formal data model and query language to express complex aggregate queries. Next, we study the compression of trajectory data, produced by moving objects, using the notions of stops and moves. We show that stops and moves are expressible in our query language and we consider a fragment of this language, consisting of regular expressions to talk about temporally ordered sequences of stops and moves. This fragment can be used to efficiently express data mining and pattern matching tasks over trajectory data. 1