September 2013 769 Recent IT technologies and online services are tremendously altering the way people create, use and share geographic information (Elwood, 2008). Enabled by the widespread use of hand-handled GPS, geo-tags, high-resolution graphics and access to the Internet and Web 2.0, spatial data can be collected and produced voluntarily by the untrained general public. This has been terme...

The analysis of temporal data has deserved a considerable attention, in particular in the analysis of time series. However, the general research on data mining seldom has focused its attention on dealing with the specific attribute – time. The discovery of temporal patterns, that reveal interesting behaviors over time, is one of such cases. In this paper, we propose a new approach to effectivel...

In sequential pattern discovery, the support of a sequence is computed as the number of data-sequences satisfying a pattern with respect to the total number of data-sequences in the database. When the items are frequently updated, the traditional way of counting support in sequential pattern mining may lead to incorrect (or, at least incomplete), conclusions. For example, if we are looking for ...

In recent years the availability of high-speed digital video cameras has motivated the study of electronic speckle pattern interferometry (ESPI) in the time domain. To this end a properly sampled temporal sequence of N-fringe patterns is used to analyze the temporal experiment. Samples of temporal speckle images must fulfill the Nyquist criteria over the time axis. When the transient phenomena ...

The following approach is used to mine for temporal-spatial patterns in large data sets. We rst present a parameterizable model for spatial-temporal sequences, then devise eecient ways to search for parameter values that will result in a good t to (at least portion of) the data. Metrics for how well the model ts the data are deened which are similar to the support and conndence used in associat...

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Online social networks enable fast and wide diffusion of rumors, which could be potential threats to the society. Understanding the rumor spreading mechanism is therefore essential. This demo presents an agent-patternbased model that can explain the spiky temporal diffusion pattern of rumors. The demo platform provides an interface allowing users to check a wide set of parameters contribute to ...

Recognizing patterns with temporal context is important for such tasks as speech recognition, motion detection and signature verification. We propose an architecture in which time serves as its own representation, and temporal context is encoded in the state of the nodes. We contrast this with the approach of replicating portions of the architecture to represent time. As one example of these id...

This paper discusses a prototype of a temporal pattern predictor, which was built on specifications derived from the descriptions of the “Ergotrix” temporal memory network in Valentino Braitenberg’s “Vehicles” (Braitenberg, 1984). The prototype was developed as a component for a control architecture for virtual characters.