The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Mining in Spatio-Temporal Databases
Abstract
Recent interest in spatio-temporal applications has been fueled by the need to discover and predict complex patterns that occur when we observe the behavior of objects in the three-dimensional space of time and spatial coordinates. Although the complex and intrinsic relationships among the spatio-temporal data limit the usefulness of conventional data mining techniques to discover the patterns in the spatio-temporal databases, they also lead to opportunities for mining new classes of patterns in spatio-temporal databases. This chapter provides a survey of the work done for mining patterns in spatial databases and temporal databases, and the preliminary work for mining patterns in spatio-temporal databases. We highlight the unique challenges of mining interesting patterns in spatio-temporal databases. We also describe two special types of spatio-temporal patterns: location-sensitive sequence patterns and geographical features for location-based service patterns.
Related Content
Nuno Silva, Pedro Sousa, Miguel Mira da Silva.
© 2019.
19 pages.
|
Ioannis Routis, Mara Nikolaidou, Nancy Alexopoulou.
© 2019.
21 pages.
|
Jeffrey S. Zanzig, Guillermo A. Francia III, Xavier P. Francia.
© 2019.
26 pages.
|
S. B. Goyal.
© 2019.
30 pages.
|
Maria João Ferreira, Fernando Moreira, Isabel Seruca.
© 2019.
24 pages.
|
Agostino Poggi, Paolo Fornacciari, Gianfranco Lombardo, Monica Mordonini, Michele Tomaiuolo.
© 2019.
21 pages.
|
Rüdiger Pryss, Manfred Reichert.
© 2019.
26 pages.
|
|
|