Emmanuel Stefanakis

Harokopion University of Athens, Athens, Attiki, Greece

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Publications (33)10.54 Total impact

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    ABSTRACT: The paper presents the project “Non-linear Digital Storytelling for the Battleship Georgios Averof” that currently takes place under the integrated action program between the German Academic Exchange Service (DAAD) and the Greek State Scholarship Foundation (I.K.Y.). The methodology applied, the objectives that the research focuses on and the first outcomes of the project are described.
    AGILE International Conference on Geographic Information Science - Geospatial Thinking; 01/2010
  • Seventh European GIS Education Seminar (EUGISES 2010); 01/2010
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    Haroula Papadaki, Eleni Gadolou, Emmanuel Stefanakis
    2nd International Workshop on Story-Telling and Educational Games (STEG'09) in conjunction with the 8th International Conference on Web-based Learning 2009 (ICWL 2009); 01/2009
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    Emmanuel Stefanakis, Poulicos Prastacos
    01/2008;
  • Emmanuel Stefanakis
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    ABSTRACT: This paper introduces DBSCAN-MO, an algorithm for density-based clustering of point objects on a planar surface with moving obstacles. This algorithm extends a well known spatial clustering method, named DBSCAN, which has been initially proposed to cluster point objects in a static space. DBSCAN-MO is able to form a set of spatio-temporal clusters and may be readily customized to complex dynamic environments. A prototype system, which implements the algorithm, developed in Java and tested through a series of synthetic datasets, is also presented.
    The European Information Society: Taking Geoinformation Science One Step Further, Proceedings of the 11th AGILE Conference, Girona, Spain, 5-8 May, 2008; 01/2008
  • E. Stefanakis
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    ABSTRACT: NET‐DBSCAN, a method for clustering the nodes of a linear network, whose edges may be temporarily inaccessible, is introduced. The new method extends the idea of a well‐known spatial clustering method, named density‐based spatial clustering of applications with noise (DBSCAN). The new algorithm is described in detail and through a series of examples. A prototype system, which implements the algorithm, developed in Java and tested through a series of synthetic networks, is also presented. Finally, the application of NET‐DBSCAN method to support real‐world situations is briefly discussed.
    International Journal of Geographical Information Science 04/2007; 21(4):427-442. · 1.61 Impact Factor
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    Emmanuel Stefanakis
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    ABSTRACT: An algorithm for scheduling the trajectory of a point object, which moves on a plane surface comprising of moving obstacles, is introduced. Different quantitative criteria may be met by the schedule, e.g., the course connecting two individual locations being the shortest in length, the least expensive, the fastest as regard to its duration, etc. A prototype system that implements the algorithm is presented. Several example scenarios are also discussed. Keywords. Spatio-temporal modeling, graphs, trajectory schedule, optimum paths, moving objects.
    Informatica 01/2006; 17:95-110. · 1.12 Impact Factor
  • Emmanuel Stefanakis, Michael Peterson
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    ABSTRACT: The convergence between Geographic Information Science and Hypermedia technology leads to the emergence of a new paradigm, named Geographic Hypermedia (GH). This chapter introduces GH by presenting the underlying concepts and tools; and highlighting the content and types of services that should be provided by a GH system. The chapter also explains the structure of the book and presents an overview of the twenty-four contributions.
    12/2005: pages 1-21;
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    Emmanuel Stefanakis
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    ABSTRACT: This paper examines the problem of clustering a set of moving points that may appear either in a dynamic mapping environment or a series of thematic map layers. An algorithm for clustering these point map objects, based on the notion of density, is proposed. The algorithm, which has been implemented and tested, is anticipated to be valuable in making use and discovering patterns from large cartographic repositories.
    01/2005;
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    Emmanuel Stefanakis
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    ABSTRACT: Various algorithms have been proposed for the determination of the optimum path(s) in line networks. Moving in space under constraints is a far more complex problem, where research has been relatively scarce. An example would be the determination of the shortest sea course between two harbors. This paper presents a graph-based approach to the problem of the optimum path(s) finding in space; and shows how it can be applied to a variety of spaces and application domains. This approach, although quantitative in nature, it may also support the piecewise qualitative path selection.
    06/2004;
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    ABSTRACT: This paper defines direction relations (e.g., north, northeast) between two-dimensional objects and shows how they can be efficiently retrieved using B-, KDB- and R- tree-based data structures. Essentially, our work studies optimisation techniques for 2D range queries that arise during the processing of direction relations. We test the efficiency of alternative indexing methods through extensive experimentation and present analytical models that estimate their performance. The analytical estimates are shown to be very close to the actual results and can be used by spatial query optimizers in order to predict the retrieval cost. In addition, we implement modifications of the existing structures that yield better performance for certain queries. We conclude the paper by discussing the most suitable method depending on the type of the range and the properties of the data.
    Data & Knowledge Engineering 08/2001; · 1.52 Impact Factor
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    Emmanuel Stefanakis, Michalis Vazirgiannis, Agnes Voisard
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    ABSTRACT: This paper is focused on the incorporation of uncertainty in modelling and reasoning issues of such systems. The proposed approach is verified in a case study related to geology maps.
    07/2000;
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    Y. Theodoridis, E. Stefanakis, T. Sellis
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    ABSTRACT: Selection and join queries are fundamental operations in database management systems (DBMS). Support for nontraditional data, including spatial objects, in an efficient manner is of ongoing interest in database research. Toward this goal, access methods and cost models for spatial queries are necessary tools for spatial query processing and optimization. We present analytical models that estimate the cost (in terms of node and disk accesses) of selection and join queries using R-tree-based structures. The proposed formulae need no knowledge of the underlying R-tree structure(s) and are applicable to uniform-like and nonuniform data distributions. In addition, experimental results are presented which show the accuracy of the analytical estimations when compared to actual runs on both synthetic and real data sets
    IEEE Transactions on Knowledge and Data Engineering 02/2000; · 1.89 Impact Factor
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    ABSTRACT: Despite the attention that direction relations, such as east, southeast etc., have attracted in several domains related to Spatial Databases and Geographic Information Systems (GIS), little work has been done on their formalization and efficient processing. In this paper we define direction relations between two-dimensional objects in different levels of qualitative resolution and we show how these relations can be efficiently retrieved in existing DBMSs using B- , KDB- and R- tree-based data structures. Since query processing involving direction relations maps into range queries in twodimensional space, our work essentially studies optimization techniques for 2D ranges. We test the efficiency of alternative indexing methods through extensive experimentation and we present analytical models that estimate their performance. The analytical estimates are proved to be very close to the actual results and can be used by spatial query optimizers in order to decide the appropriate data struc...
    03/1999;
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    Emmanuel Stefanakis, Timos Sellis
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    ABSTRACT: The methods used in commercial GIS packages for both the representation and analysis of geographic data are inadequate, because they do not handle uncertainty. This leads to information loss and inaccuracy in analysis with adverse consequences in the spatial decision-making process. The incorporation of fuzzy set methodologies into a DBMS repository for the application domain of GIS should be beneficial and will improve its level of intelligence. Focusing on this direction the paper addresses both a representation and a reasoning issue. Specifically, it extends a general spatial data model to deal with the uncertainty of geographic entities, and shows how the standard data interpretation operations available in GIS packages may be extended to support the fuzzy spatial reasoning. Representative geographic operations, such as the fuzzy overlay, fuzzy distance and fuzzy select, are examined, while a real world situation involving spatial decision making is presented.
    01/1999;
  • Emmanuel Stefanakis, Michalis Vazirgiannis, Timos K. Sellis
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    ABSTRACT: It has been recently recognized that fuzzy set theory provides useful concepts and tools for both the representation and analysis of the uncertainty related to geographical data. Hence the incorporation of fuzzy set methodologies into a DBMS repository for the application domain of GIS should be beneficial and will improve its level of intelligence. Focusing in this area the paper addresses both a representation and a reasoning issue. Specifically, it extends a general spatial data model to deal with the uncertainty of geographical entities, and shows how the standard data interpretation operations available in GIS packages may be extended to support the fuzzy spatial reasoning. Representative geographical operations, suchas the fuzzy overlay, fuzzy distance and fuzzy select, are examined, while several real world examples are given.
    International Journal of Geographical Information Science 01/1999; 13:657-675. · 1.61 Impact Factor
  • Y. Theodoridis, E. Stefanakis, T. Sellis
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    ABSTRACT: The join query is one of the fundamental operations in database management systems (DBMSs). Modern DBMSs should be able to support non traditional data, including spatial objects, in an efficient manner. Towards this goal, spatial data structures can be adopted in order to support the execution of join queries on sets of multidimensional data. The paper introduces analytical models that estimate the cost (in terms of node or disk accesses) of join queries involving two multidimensional indexed data sets using R tree based structures. In addition, experimental results are presented, which show the accuracy of the analytical estimations when compared to actual runs on both synthetic and real data sets. It turns out that the relative error rarely exceeds 15% for all combinations, a fact that makes the proposed cost models useful tools for efficient spatial query optimization
    Data Engineering, 1998. Proceedings., 14th International Conference on; 03/1998
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    [Show abstract] [Hide abstract]
    ABSTRACT: Despite the attention that direction relations, such as east, southeast etc., have attracted in several domains related to Spatial Databases and Geographic Information Systems (GIS), little work has been done on their formalization and efficient processing. In this paper we define direction relations between two-dimensional objects in different levels of qualitative resolution and we show how these relations can be efficiently retrieved in existing DBMSs using B- , KDB- and R- tree-based data structures. Since query processing involving direction relations maps into range queries in two- dimensional space, our work essentially studies optimization techniques for 2D ranges. We test the efficiency of alternative indexing methods through extensive experimentation and we present analytical models that estimate their performance. The analytical estimates are proved to be very close to the actual results and can be used by spatial query optimizers in order to decide the appropriate data structure for each type of range query. Although for our experiments we define a small set of representative relations motivated by geographic applications, the results of this paper are directly applicable to any type of direction relations (or range queries in general) that may arise in different application domains.
    Data Knowl. Eng. 01/1998; 27:313-336.
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    Emmanuel Stefanakis, Timos Sellis
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    ABSTRACT: Much attention has been devoted in the past to support classes of applications which are not well served by conventional database systems. Focusing on the application domain of geographic information systems (GIS), several architectural approaches have been proposed to implement commercial or prototype systems and satisfy the urgent needs for geographic data handling. However, those systems suffer from several limitations because they either perform much processing on an application layer, which is at the top of the database management system (DBMS), or the underlying data models are not rich enough to represent the spatial dimension of geographic entities. This study examines the spatial operations that should be provided by a DBMS for the application domain of GIS and focuses on the various techniques which may be used to support the efficient execution of both simple operations and composite procedures that involve the spatial dimension of geographic entities.
    Cartography and Geographic Information Science - CARTOGR GEOGR INF SCI. 01/1998; 25(1):16-32.
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    Yannis Theodoridis, Emmanuel Stefanakis, Timos Sellis
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    ABSTRACT: : The join query is one of the fundamental operations in Data Base Management Systems (DBMSs). Modern DBMSs should be able to support non-traditional data, including spatial objects, in an efficient manner. Towards this goal, spatial data structures can be adopted in order to support the execution of join queries on sets of multidimensional data. This paper introduces analytical models that estimate the cost (in terms of node or disk accesses) of join queries involving two multidimensional indexed data sets using R-tree-based structures. In addition, experimental results are presented, which show the accuracy of the analytical estimations when compared to actual runs on both synthetic and real data sets. It turns out that the relative error rarely exceeds 15% for all combinations, a fact that makes the proposed cost models useful tools for efficient spatial query optimization. 1. Introduction A Spatial Data Base Management System (SDBMS) should offer appropriate data types and query ...
    12/1997;