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66
A model for enriching trajectories with semantic geographical information
 in ‘ACMGIS’, ACM
, 2007
"... The collection of moving object data is becoming more and more common, and therefore there is an increasing need for the efficient analysis and knowledge extraction of these data in different application domains. Trajectory data are normally available as sample points, and do not carry semantic info ..."
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Cited by 49 (8 self)
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The collection of moving object data is becoming more and more common, and therefore there is an increasing need for the efficient analysis and knowledge extraction of these data in different application domains. Trajectory data are normally available as sample points, and do not carry semantic information, which is of fundamental importance for the comprehension of these data. Therefore, the analysis of trajectory data becomes expensive from a computational point of view and complex from a user’s perspective. Enriching trajectories with semantic geographical information may simplify queries, analysis, and mining of moving object data. In this paper we propose a data preprocessing model to add semantic information to trajectories in order to facilitate trajectory data analysis in different application domains. The model is generic enough to represent the important parts of trajectories that are relevant to the application, not being restricted to one specific application. We present an algorithm to compute the important parts and show that the query complexity for the semantic analysis of trajectories will be significantly reduced with the proposed model.
Algorithms for Moving Objects Databases
"... Whereas earlier work on spatiotemporal databases generally focused on geometries changing in discrete steps, the emerging area of moving objects databases supports geometries changing continuously. Two important abstractions are moving point and moving region, modeling objects for which only the ti ..."
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Cited by 46 (12 self)
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Whereas earlier work on spatiotemporal databases generally focused on geometries changing in discrete steps, the emerging area of moving objects databases supports geometries changing continuously. Two important abstractions are moving point and moving region, modeling objects for which only the timedependent position, or also the shape and extent are relevant, respectively. Examples of the first kind of moving entity are all kinds of vehicles, aircraft, people, or animals; of the latter hurricanes, forest res, forest growth, or oil spills in the sea. The goal is to develop data models and query languages as well as DBMS implementations supporting such entities, enabling new kinds of database applications. In earlier work we have proposed an approach based on abstract data types. Hence, moving point or moving region are viewed as data types with suitable operations. For example, a moving point might be projected into the plane, yielding a curve, or a moving region be mapped to a function describing the development of its size, yielding a realvalued function. A careful design of a system of types and operations (an algebra) has been presented, emphasizing completeness, closure, consistency and genericity. This design was given at an abstract level, defining, for example, geometries in terms of infinite point sets. In the next step, a discrete model was presented, o ering nite representations and data structures for all the types of the abstract model. The present paper provides the final step towards implementation by studying and developing systematically algorithms for (a large subset of) the operations. Some of them are relatively straightforward; others are quite complex. Algorithms are meant to be used in a database context; we also address...
On trip planning queries in spatial databases
 In SSTD
, 2005
"... In this paper we discuss a new type of query in Spatial Databases, called the Trip Planning Query (TPQ). Given a set of points of interest P in space, where each point belongs to a specific category, a starting point S and a destination E, TPQ retrieves the best trip that starts at S, passes through ..."
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Cited by 40 (1 self)
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In this paper we discuss a new type of query in Spatial Databases, called the Trip Planning Query (TPQ). Given a set of points of interest P in space, where each point belongs to a specific category, a starting point S and a destination E, TPQ retrieves the best trip that starts at S, passes through at least one point from each category, and ends at E. For example, a driver traveling from Boston to Providence might want to stop to a gas station, a bank and a post office on his way, and the goal is to provide him with the best possible route (in terms of distance, traffic, road conditions, etc.). The difficulty of this query lies in the existence of multiple choices per category. In this paper, we study fast approximation algorithms for TPQ in a metric space. We provide a number of approximation algorithms with approximation ratios that depend on either the number of categories, the maximum number of points
A Clusteringbased Approach for Discovering Interesting Places in Trajectories
"... Because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. Most existing works have focused on the geometric properties of trajectories, but recently emerged the concept of semantic trajectories, in which ..."
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Cited by 37 (6 self)
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Because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. Most existing works have focused on the geometric properties of trajectories, but recently emerged the concept of semantic trajectories, in which the background geographic information is integrated to trajectory sample points. In this new concept, trajectories are observed as a set of stops and moves, where stops are the most important parts of the trajectory. Stops and moves have been computed by testing the intersections of trajectories with a set of geographic objects given by the user. In this paper we present an alternative solution with the capability of finding interesting places that are not expected by the user. The proposed solution is a spatiotemporal clustering method, based on speed, to work with single trajectories. We compare the two different approaches with experiments on real data and show that the computation of stops using the concept of speed can be interesting for several applications.
Location and TimeBased Information Delivery in Tourism
 In Proc. 8 th International Symposium in Spatial and Temporal Databases (SSTD
, 2003
"... Today's mobile devices allow end users to get information related to a particular domain based on their current location, such as the fastest route to the nearest drugstore. However, in such LocationBased Services (LBS), richer and more targeted information is desirable. In many application ..."
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Cited by 32 (10 self)
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Today's mobile devices allow end users to get information related to a particular domain based on their current location, such as the fastest route to the nearest drugstore. However, in such LocationBased Services (LBS), richer and more targeted information is desirable. In many applications, end users would like to be notified about relevant events or places to visit in the near future according to their profile. They also do not wish to get the same information many times unless they explicitly ask for it. In this paper, we describe our system, TIP (Tourism Information Provider), which delivers various types of information to mobile devices based on location, time, profile of end users, and their "history", i.e., their accumulated knowledge. The system hinges on a hierarchical semantic geospatial model as well as on an Event Notification System (ENS).
Shapebased Similarity Query for Trajectory of Mobile Objects
 Proceedings of MDM
, 2003
"... Abstract. In this paper, we describe an efficient indexing method for a shapebased similarity search of the trajectory of dynamically changing locations of people and mobile objects. In order to manage trajectories in database systems, we define a data model of trajectories as directed lines in a s ..."
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Cited by 28 (2 self)
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Abstract. In this paper, we describe an efficient indexing method for a shapebased similarity search of the trajectory of dynamically changing locations of people and mobile objects. In order to manage trajectories in database systems, we define a data model of trajectories as directed lines in a space, and the similarity between trajectories is defined as the Euclidean distance between directed discrete lines. Our proposed similarity query can be used to find interested patterns embedded into the trajectories, for example, the trajectories of mobile cars in a city may include patterns for expecting traffic jams. Furthermore, we propose an efficient indexing method to retrieve similar trajectories for a query by combining a spatial indexing technique (R +Tree) and a dimension reduction technique, which is called PAA (Piecewise Approximate Aggregate). The indexing method can efficiently retrieve trajectories whose shape in a space is similar to the shape of a candidate trajectory from the database. 1
Querying continuous functions in a database system
 In ACM SIGMOD
, 2008
"... Many scientific, financial, data mining and sensor network applications need to work with continuous, rather than discrete data e.g., temperature as a function of location, or stock prices or vehicle trajectories as a function of time. Querying raw or discrete data is unsatisfactory for these applic ..."
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Cited by 26 (0 self)
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Many scientific, financial, data mining and sensor network applications need to work with continuous, rather than discrete data e.g., temperature as a function of location, or stock prices or vehicle trajectories as a function of time. Querying raw or discrete data is unsatisfactory for these applications – e.g., in a sensor network, it is necessary to interpolate sensor readings to predict values at locations where sensors are not deployed. In other situations, raw data can be inaccurate owing to measurement errors, and it is useful to fit continuous functions to raw data and query the functions, rather than raw data itself – e.g., fitting a smooth curve to noisy sensor readings, or a smooth trajectory to GPS data containing gaps or outliers. Existing databases do not support storing or querying continuous functions, short of bruteforce discretization of functions into a collection of tuples. We present FunctionDB, a novel database
Mobility patterns
 GeoInformatica
, 2004
"... We present a data model for tracking mobile objects and reporting the result of continuous queries. The model relies on a discrete view of the spatiotemporal space, where the 2D space and the time axis are respectively partitioned in a finite set of userdefined areas and in constantsize intervals. ..."
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Cited by 23 (0 self)
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We present a data model for tracking mobile objects and reporting the result of continuous queries. The model relies on a discrete view of the spatiotemporal space, where the 2D space and the time axis are respectively partitioned in a finite set of userdefined areas and in constantsize intervals. We define a query language to retrieve objects that match mobility patterns describing a sequence of moves and discuss evaluation techniques to maintain incrementally the result of queries. 1
Indexing the Trajectories of Moving Objects
 IEEE Data Engineering Bulletin
, 2002
"... The domain of spatiotemporal applications is a treasure trove of new types of data and queries. In this work, the focus is on a spatiotemporal subdomain, namely the trajectories of moving point objects. We examine the issues posed by this type of data with respect to indexing and point out existing ..."
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Cited by 21 (4 self)
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The domain of spatiotemporal applications is a treasure trove of new types of data and queries. In this work, the focus is on a spatiotemporal subdomain, namely the trajectories of moving point objects. We examine the issues posed by this type of data with respect to indexing and point out existing approaches and research directions. An important aspect of movement is the scenario in which it occurs. Three different scenarios, namely unconstrained movement, constrained movement, and movement in networks are used to categorize various indexing approaches. Each of these scenarios give us different means to either simplify indexing, or to improve the overall query processing performance.
Optimization and evaluation of shortest path queries
 VLDB J
"... We investigate the problem of how to evaluate efficiently a collection of shortest path queries on massive graphs that are too big to fit in the main memory. To evaluate a shortest path query efficiently, we introduce two pruning algorithms. These algorithms differ on the extent of materialization o ..."
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Cited by 20 (0 self)
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We investigate the problem of how to evaluate efficiently a collection of shortest path queries on massive graphs that are too big to fit in the main memory. To evaluate a shortest path query efficiently, we introduce two pruning algorithms. These algorithms differ on the extent of materialization of shortest path cost and on how the search space is pruned. By grouping shortest path queries properly, batch processing improves the performance of shortest path query evaluation. Extensive study is also done on fragment sizes, cache sizes and query types that we show that affect the performance of a diskbased shortest path algorithm. The performance and scalability of proposed techniques are evaluated with large road systems in the Eastern United States. To demonstrate that the proposed diskbased algorithms are viable, we show that their search times are significant better than that of mainmemory Dijkstra’s algorithm. 1