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ABSTRACT: An increasing amount of trajectory data is being annotated with text
descriptions to better capture the semantics associated with locations. The
fusion of spatial locations and text descriptions in trajectories engenders a
new type of top-$k$ queries that take into account both aspects. Each
trajectory in consideration consists of a sequence of geo-spatial locations
associated with text descriptions. Given a user location $\lambda$ and a
keyword set $\psi$, a top-$k$ query returns $k$ trajectories whose text
descriptions cover the keywords $\psi$ and that have the shortest match
distance. To the best of our knowledge, previous research on querying
trajectory databases has focused on trajectory data without any text
description, and no existing work has studied such kind of top-$k$ queries on
trajectories. This paper proposes one novel method for efficiently computing
top-$k$ trajectories. The method is developed based on a new hybrid index,
cell-keyword conscious B$^+$-tree, denoted by \cellbtree, which enables us to
exploit both text relevance and location proximity to facilitate efficient and
effective query processing. The results of our extensive empirical studies with
an implementation of the proposed algorithms on BerkeleyDB demonstrate that our
proposed methods are capable of achieving excellent performance and good
scalability.
05/2012;
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Scientific and Statistical Database Management, 22nd International Conference, SSDBM 2010, Heidelberg, Germany, June 30 - July 2, 2010. Proceedings; 01/2010
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VLDB J. 01/2010; 19:181-201.
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ABSTRACT: In this work, we present our implementation for managing moving objects on top of a popular relational database system MySQL, namely SpADE (spatio-temporal autonomic database engine for managing moving objects). In our SpADE system, non-static entities like vehicles and pedestrians are abstracted as moving objects. They obtain positioning information with GPS (Global Positioning System) receivers installed, and are able to communicate via wireless network with the server, sending queries to and receiving results from it. The server is responsible for managing moving object information and processing queries from mobile users. By employing the industry standard JDBC for the data access, our server can also support providing services for other application interfaces such as the Web.
Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on; 05/2007
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Advances in Spatial and Temporal Databases, 10th International Symposium, SSTD 2007, Boston, MA, USA, July 16-18, 2007, Proceedings; 01/2007
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Advances in Spatial and Temporal Databases, 10th International Symposium, SSTD 2007, Boston, MA, USA, July 16-18, 2007, Proceedings; 01/2007
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ABSTRACT: The literature on skyline algorithms has so far dealt mainly with queries of static query points over static data sets. With the increasing number of mobile service applications and users, however, the need for continuous skyline query processing has become more pressing. A continuous skyline query involves not only static dimensions, but also the dynamic one. In this paper, we examine the spatiotemporal coherence of the problem and propose a continuous skyline query processing strategy for moving query points. First, we distinguish the data points that are permanently in the skyline and use them to derive a search bound. Second, we investigate the connection between the spatial positions of data points and their dominance relationship, which provides an indication of where to find changes in the skyline and how to maintain the skyline continuously. Based on the analysis, we propose a kinetic-based data structure and an efficient skyline query processing algorithm. We concisely analyze the space and time costs of the proposed method and conduct an extensive experiment to evaluate the method. To the best of our knowledge, this is the first work on continuous skyline query processing
IEEE Transactions on Knowledge and Data Engineering 01/2007; 18(12):1645-1658. · 1.66 Impact Factor
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ABSTRACT: Skyline queries are well suited when retrieving data according to multiple criteria. While most previous work has assumed a centralized setting this paper considers skyline querying in a mobile and distributed setting, where each mobile device is capable of holding only a portion of the whole dataset; where devices communicate through mobile ad hoc networks; and where a query issued by a mobile user is interested only in the users local area, although a query generally involves data stored on many mobile devices due to the storage limitations. We present techniques that aim to reduce the costs of communication among mobile devices and reduce the execution time on each single mobile device. For the former, skyline query requests are forwarded among mobile devices in a deliberate way, such that the amount of data to be transferred is reduced. For the latter, specific optimization measures are proposed for resource-constrained mobile devices. We conduct extensive experiments to show that our proposal performs efficiently in real mobile devices and simulated wireless ad hoc networks.
Data Engineering, 2006. ICDE '06. Proceedings of the 22nd International Conference on; 05/2006
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IEEE Trans. Knowl. Data Eng. 01/2006; 18:1645-1658.
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Proceedings of the 22nd International Conference on Data Engineering, ICDE 2006, 3-8 April 2006, Atlanta, GA, USA; 01/2006
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13th ACM International Workshop on Geographic Information Systems, ACM-GIS 2005, November 4-5, 2005, Bremen, Germany, Proceedings; 01/2005
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Proceedings of the ACM SIGMOD International Conference on Management of Data, Paris, France, June 13-18, 2004; 01/2004
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ABSTRACT: Skyline queries are often used on data sets in multi-dimensional space for many decision-making applications. Traditionally, a point p is said to dominate another point q if, for all dimension, it is no worse than q and is better on at least one dimension. Therefore, the skyline of a data set consists of all points not dominated by any other point. To better cater to application requirements such as controlling the size of the skyline or handling data sets that are not well-structured, various works have been proposed to extend the definition of skyline based on variants of the dominance relationship. However, it is difficult to implement each of these variants separately in a system setting and instead effort must be made to provide a general framework so that these specific implementations can be easily materialized over the framework. In this paper, a generalized framework is proposed for this purpose. Our framework explicitly and care-fully examines the various properties that should be preserved in a variant of the dominance relationship so that: (1) the original advantages of skyline can be maintained while adaptivity to application semantics is also catered to and (2) computational complexity is al-most unaffected. We prove that traditional dominance is the only relationship satisfying all desirable proper-ties and present some new dominance relationships to illustrate that other skyline variants always have their tradeoff in relaxing some of the properties. We then de-veloped generic algorithms that compute skyline vari-ants subject to the constraints that certain properties are relaxed and illustrate the use of our framework in computing of skyline over datasets with missing values. Extensive experimental results are presented to evalu-ate the efficiency and effectiveness of our framework.
