Victor Teixeira de Almeida

FernUniversität in Hagen, Hagen, North Rhine-Westphalia, Germany

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Publications (20)2.4 Total impact

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    V. Teixeira de Almeida, R. Hartmut Giiting, C. Duntgen
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    ABSTRACT: Traditional indexing techniques are not well suited for complex data types such as spatial, spatio-temporal, and multimedia data types, where an instance is a composite of multiple components. In this paper we propose two indexing techniques that allow the parts of a composite object to be indexed separately, called multiple entry indexing and double indexing. We present the implementation of these approaches in the SECONDO extensible database system. The improvements in terms of performance of both approaches presented in this paper are shown in an experimental evaluation.
    Database Engineering and Applications Symposium, 2007. IDEAS 2007. 11th International; 10/2007
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    V. Teixeira de Almeida, R. Hartmut Guting, T. Behr
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    ABSTRACT: Representing descriptions of movements in databases and querying them is a basic capability required in mobile data management. In this demonstration, we show for the first time a prototype implementing a data model and query language for moving objects (trajectories) completely integrated into a DBMS environment, including query optimization and user interface issues such as animation.
    Mobile Data Management, 2006. MDM 2006. 7th International Conference on; 06/2006
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    Victor Teixeira de Almeida
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    ABSTRACT: Moving objects databases have become an intensive field of research in recent years with many applications such as location-based services, trac monitoring, fleet management, etc. Most of the works in the literature assume free movement in the 2-dimensional space, al- though in some cases, the objects move within spatially embedded net- works, e.g. vehicles in highways and trains in railways. Moreover, these works are focused on isolated aspects such as ecient query processing with specialized index structures. The aim of this PhD. project is to present a complete database management system for eciently storing and querying moving objects in networks, providing a comprehensive data model supporting the description of complete histories of move- ment, index structures for ecient query processing, an extended model handling uncertainty, and a complete integrated implementation as an algebra inside the Secondo extensible database system.
    Current Trends in Database Technology - EDBT 2006, EDBT 2006 Workshops PhD, DataX, IIDB, IIHA, ICSNW, QLQP, PIM, PaRMA, and Reactivity on the Web, Munich, Germany, March 26-31, 2006, Revised Selected Papers; 01/2006
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    Victor Teixeira de Almeida, Ralf Hartmut Güting
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    ABSTRACT: One of the most important kinds of queries in Spatial Network Databases (SNDB) to support Location-Based Services (LBS) is the k-Nearest Neighbors (k-NN) query. Given a point in a network, e.g. a location of a car on a road network, and a set of points of in- terests, e.g. hotels, gas stations, etc., the k-NN query returns the k points of interest closest to the query point. The network distance is used in such a query instead of the Euclidean distance. Dijk- stra's algorithm is a well known solution to this problem. In this paper, we propose a storage schema with a set of index structures to support an efficient execution of a slightly modified version of the Dijkstra's algorithm. We show in an experimental evaluation with generated data sets that our proposal is more efficient than the state-of-the-art solution to this problem.
    Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), Dijon, France, April 23-27, 2006; 01/2006
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    Victor Teixeira de Almeida
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    ABSTRACT: One of the most important kind of queries in spatial data-bases to support location-based services (LBS) is the continuous nearest neighbors (CNN) query. Given a spatial data set of points of interest and a moving query point q, the CNN query partitions q into a set of adjacent disjoint intervals associated with their nearest points of interest. Existing solutions to this problem are known to be sub-optimal in terms of disk accesses. In this paper, we present an algorithm to compute the CNN query that is I/O optimal. With an experimental evaluation, we show that not only the number of disk accesses is reduced with the optimal algorithm, but also the CPU performance is improved, in some cases.
    14th ACM International Symposium on Geographic Information Systems, ACM-GIS 2006, November 10-11, 2006, Arlington, Virginia, USA, Proceedings; 01/2006
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    Ralf Hartmut Güting, Victor Teixeira de Almeida, Zhiming Ding
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    ABSTRACT: Moving objects databases have become an important research issue in recent years. For modeling and querying moving objects, there exists a comprehensive framework of abstract data types to describe objects moving freely in the 2D plane, providing data types such as moving point or moving region. However, in many applications people or vehicles move along transportation networks. It makes a lot of sense to model the network explicitly and to describe movements relative to the network rather than unconstrained space, because then it is much easier to formulate in queries relationships between moving objects and the network. Moreover, such models can be better supported in indexing and query processing. In this paper, we extend the ADT approach by modeling networks explicitly and providing data types for static and moving network positions and regions. In a highway network, example entities corresponding to these data types are motels, construction areas, cars, and traffic jams. The network model is not too simplistic; it allows one to distinguish simple roads and divided highways and to describe the possible traversals of junctions precisely. The new types and operations are integrated seamlessly into the ADT framework to achieve a relatively simple, consistent and powerful overall model and query language for constrained and unconstrained movement.
    The VLDB Journal 01/2006; 15:165-190. · 1.40 Impact Factor
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    Thomas Behr, Victor Teixeira de Almeida, Ralf Hartmut Güting
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    ABSTRACT: In the real world, lots of objects with changing position can be found. Some of them repeat the same movement several times, called periodic movements. Examples include airplanes, trains, planets, and marine turtles. This paper describes a model for representing the periodic movements to be stored in a database system, exploiting the information about the repetitions. The model is generic enough to represent any kind of movement, not being restricted to objects with repetitions in their movement. We present algorithms to detect the repetitions and to convert to the periodic representation as well as the implementation of some operations on such representation. We show, in an experimental evaluation against the so-called flat representation, that the approach presented in this paper significantly improves the performance of query processing in a database system when dealing with objects with some periodic movement. We also show that, for the worst case where the objects do not follow any periodic movement at all, our approach still performs acceptably.
    14th ACM International Symposium on Geographic Information Systems, ACM-GIS 2006, November 10-11, 2006, Arlington, Virginia, USA, Proceedings; 01/2006
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    ABSTRACT: The goal of SECONDO is to provide a "generic" database system frame that can be filled with implementations of various DBMS data models. SECONDO was intended originally as a platform for implementing and experimenting with new kinds of data models, especially to support spatial, spatio-temporal, and graph database models. We now feel, SECONDO has a clean architecture, and it strike a reasonable balance between simplicity and sophistication. Since all the source code is accessible and to a large extent comprehensible for students, we believe it is also an excellent tool for teaching database architecture and implementation concepts. SECONDO runs on Windows, Linux, and Solaris platforms, and consists of three major components SECONDO kernel, optimizer, and graphical user interface.
    Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on; 05/2005
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    Victor Teixeira de Almeida, Ralf Hartmut Güting
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    ABSTRACT: The management of moving objects has been intensively studied in recent years. A wide and increasing range of database applications has to deal with spatial objects whose position changes continuously over time, called moving objects. The main interest of these applications is to efficiently store and query the positions of these continuously moving objects. To achieve this goal, index structures are required. The main proposals of index structures for moving objects deal with unconstrained 2-dimensional movement. Constrained movement is a special and a very important case of object movement. For example, cars move in roads and trains in railroads. In this paper we propose a new index structure for moving objects on networks, the MON-Tree. We describe two network models that can be indexed by the MON-Tree. The first model is edge oriented, i.e., the network consists of nodes and edges and there is a polyline associated to each edge. The second one is more suitable for transportation networks and is route oriented, i.e., the network consists of routes and junctions. In this model, a polyline also serves as a representation of the routes. We propose the index in terms of the basic algorithms for insertion and querying. We test our proposal in an extensive experimental evaluation with generated data sets using as underlying networks the roads of Germany. In our tests, the MON-Tree shows good scalabiliy and outperforms the competing index structures in updating (index creation) as well as in querying.
    GeoInformatica 02/2005; 9(1):33-60. · 1.00 Impact Factor
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    Victor Teixeira de Almeida, Ralf Hartmut Güting
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    ABSTRACT: The management of moving objects has been intensively studied in the recent years. A wide and increasing range of database applications has to deal with spatial objects whose position changes continuously over time, called moving objects. Due to the continuous and unpredictable nature of the movements, they cannot be precisely stored in a database, and therefore objects' positions are sampled, and between these sampled positions interpolation is used. This sampling/interpolation approach results in uncertainty in the objects' positions in the whole trajectory of the moving objects. In this paper, we try to analyze this problem about uncertainty when the movement is restricted to a network. Examples of such movements are cars in highways and trains in railroads. The uncertainty problem is simpler in such cases compared to the free movement in 2-dimensional space. We describe the geometry of the uncertain trajectories of the objects with movement constrained to networks, an extension to the framework in [18, 16] to support uncertainty, as well as some implementation considerations using Secondo, an extensible database system that supports non-standard applications.
    13th ACM International Workshop on Geographic Information Systems, ACM-GIS 2005, November 4-5, 2005, Bremen, Germany, Proceedings; 01/2005
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    V.T. de Almeida, R.H. Guting
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    ABSTRACT: The management of moving objects has been intensively studied in recent years. A wide and increasing range of database applications has to deal with spatial objects whose position changes continuously over time. The main interest of these applications is to efficiently store and query the positions of these objects. To achieve this goal, index structures are required. Most of the proposals of index structures for moving objects deal with unconstrained 2-dimensional movement. The constrained movement is a special and a very important case of object movement. In this paper we propose a new index structure for moving objects in networks, the MON-Tree. We tested our proposal in an experimental evaluation with generated data sets. The MON-Tree showed good scalability when increasing the number of objects and time units in the index structure, and the query window and time interval in querying.
    Scientific and Statistical Database Management, 2004. Proceedings. 16th International Conference on; 07/2004
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    ABSTRACT: We describe SECONDO, an extensible DBMS platform suitable for building research prototypes and for teaching architecture and implementation of database systems. It does not have a fixed data model, but is open for implementation of new models. SECONDO consists of three major components which can be used together or independently: (i) the kernel, which offers query processing over a set of implemented algebras, each offering some type constructors and operators, (ii) the optimizer, which implements the essential part of an SQL-like language, and (iii) the graphical user interface which is extensible by viewers for new data types and which provides a sophisticated viewer for spatial and spatio-temporal (moving) objects. Examples of algebras implemented in SECONDO are relations, spatial data types, R-trees, or midi objects (music files), each with suitable operations. The kernel is extensible by algebras, the optimizer by optimization rules and cost functions, and the GUI by viewers and display functions.
    04/2004;
  • Victor Teixeira de Almeida, Ralf Hartmut Güting
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    ABSTRACT: Victor Teixeira de Almeida Ralf Hartmut GutingPraktische Informatik IVFernuniversitat Hagen, D-58084 Hagen, Germany{victor.almeida,rhg}@fernuni-hagen.deAbstractstudied in recent years. A wide and increasingrange of database applications has to deal with spatial objectswhose position changes continuously over time. Themain interest of these applications is to e#ciently storeand query the positions of these objects. To achieve thisgoal, index structures are required. Most of the...
    Proceedings of the 16th International Conference on Scientific and Statistical Database Management (SSDBM 2004), 21-23 June 2004, Santorini Island, Greece; 01/2004
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    Geraldo Zimbrao, Jano Moreira de Souza, Victor Teixeira de Almeida
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    ABSTRACT: Among other operations, a spatiotemporal DBMS should efficiently answer the spatiotemporal join. This paper presents an evaluation of spatiotem- poral join algorithms using these new structures, particularly a partially persis- tent R-Tree called Temporal R-Tree and the 2+3D R-Tree. Starting from spatial join algorithms, we present algorithms for processing spatiotemporal joins over time instants and intervals on both spatiotemporal data structures. Finally, we implement and test these new algorithms with a couple of generated spatiotem- poral data sets. Our experiments show that our algorithmsperformance is good even in extreme cases, showing its good scalability - especially for the TR- Tree.
    Database Systems for Advances Applications, 9th International Conference, DASFAA 2004, Jeju Island, Korea, March 17-19, 2004, Proceedings; 01/2004
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    ABSTRACT: Mining association rules in a market basket database is a well stated problem, and there are a number of approaches to deal with this problem. However, there are many circumstances where the current techniques are not adequate. An interesting one is to mine rules about items that have seasonal selling rate, which is called calendar-based association rule mining. Another one is to mine association rules about items introduced into or removed from the database, that is, to consider the items' lifespan. Although there are some works about these problems, no one considers both problems together -- but in real market basket databases it is crucial to consider both the items' lifespan and its seasonality. This work states this problem in detail, and we present an example where other algorithms fail to discover important (quite evident) association rules. Also, we present an extended version of the calendarbased algorithm to mine these kinds of association rules.
    08/2002;
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    ABSTRACT: It's a well-known fact that new GIS applications need to keep track of temporal information. However, the most widely used spatial index, the R-Tree and its variants, do not preserve the evolution of bounding boxes. Some new indexing structures were proposed in the literature that allows the retrieving of present and past states of data. In this paper we evaluate the most popular indexes structure to perform spatiotemporal queries. Spatiotemporal queries can be grouped in two classes: queries involving time instants and queries involving time intervals. We point out which are the best indexes for each class. In this paper we also propose a new data structure termed the Temporal R-Tree, which combines several features of Becker et al. Multi-Version B-Tree with the spatial indexing characteristics of the R-Tree. We have shown that the Temporal R-Tree is the only structure suitable for efficiently supporting both classes of queries - the other structures proposed in the literature are fine for just one of these classes. A number of comparative queries on several data sets were performed to show the scalability of the Temporal R-Tree. Our experiments show that its performance and space utilization are very good even on worst cases, showing that the Temporal R-Tree is by now the best choice for indexing spatiotemporal data.
    07/2002;
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    Geraldo Zimbrao, Jano Moreira de Souza, Victor Teixeira de Almeida
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    ABSTRACT: It's a well-known fact that the new GIS applications need to keep track of temporal information. Among other operations, a spatiotemporal DBMS should efficiently answer the spatiotemporal join. The best-known spatial index structure, the R-Tree (and its variants), does not preserve the MBRs' evolution. New indexing structures were proposed in the literature that allows the retrieving of present and past states of data, and most of them are R-Tree based. This paper presents a first study of spatiotemporal join processing using these new structures, particularly a partially persistent R-Tree called Temporal R-Tree and the 2+3D R-Tree. Starting from spatial join algorithms, we present algorithms for processing spatiotemporal joins over time instants and intervals on both spatiotemporal structures. Then, we propose some improvements that lead to a better performance and try to show the correctness of our algorithms. Finally, we implement and test these new algorithms with some spatiotemporal data sets. Our experiments shows that our algorithms performance is good even on extreme cases, like datasets with many changes, showing its good scalability - especially for the TR-Tree. In addition, with minor adaptations, the main ideas of our algorithm can be used for evaluating joins using other partially persistent structures, like the MVB-Tree.
    XVI Simpósio Brasileiro de Banco de Dados, 1-3 Outubro 2001, Rio de Janeiro, Brasil, Anais/Proceedings.; 01/2001
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    Geraldo Zimbrão, Jano Moreira, De Souza, Victor Teixeira De Almeida
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    ABSTRACT: It's a well-known fact that the new GIS applications need to keep track of temporal information. However, the most known spatial index structure, the R-Tree and its variants, does not preserve the MBRs evolution. A first but inefficient approach is to add one dimension to data space in order to store time. In this work, we propose an alternative approach: a new index structure called Temporal R-Tree that deals with spatiotemporal data. The Temporal R-Tree, or TR-Tree, allows the retrieving of present and past states of data. There is little data duplication, which is guaranteed by the block copying mechanism. The retrieving time is comparable to the original R-Tree.

Publication Stats

318 Citations
2.40 Total Impact Points

Top Journals

Institutions

  • 2005–2007
    • FernUniversität in Hagen
      Hagen, North Rhine-Westphalia, Germany
  • 2002
    • Federal University of Rio de Janeiro
      • Programa de Engenharia de Sistemas e Computação
      Rio de Janeiro, Rio de Janeiro, Brazil