Spatiotemporal Data Mining: Issues, Tasks And Applications

K, Venkateswara Rao

doi:10.5121/ijcses.2012.3104

Cited by 41 publications

(2 citation statements)

References 38 publications

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“…Issues related to the spatiotemporal data depiction was presented in [6] for challenges associated with the spatiotemporal data depiction, analysis, mining and information visualization. Different types of data mining tasks that included association rules, classification and clustering for measuring the respective information from spatiotemporal datasets were examined and reviewed.…”

Section: Literature Reviewmentioning

confidence: 99%

An Optimized User Behavior Prediction Model Using Genetic Algorithm on Mobile Web Structure

2015

KSII TIIS

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Section: Literature Reviewmentioning

confidence: 99%

An Optimized User Behavior Prediction Model Using Genetic Algorithm on Mobile Web Structure

2015

KSII TIIS

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“…Trajectory data mining is the process of inte resting, useful knowledge and patterns discove ry in large data sets of objects` motion history. The mathematical apparatus of spatialtemporal ana lysis methods is used to study the trajectories of motion [1][2][3]. In [4] the authors divided the me thods into two categories: primary (clustering, clas sification) and secondary (pattern mining, outlier detection, prediction) and showed relationships between them.…”

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Information Technology for Trajectory Data Mining

et al. 2021

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Introduction. Advanced technologies allow almost continuous tracking and recording the movement of objects inspace and time. Detecting interesting patterns in these data, popular routes, habits, and anomalies in object motion and understanding mobility behaviors are actual tasks in different application areas such as marketing, urban planning, transportation, biology, ecology, etc.Problem Statement. In order to obtain useful information from trajectories of moving objects, it is important to develop and to improve mathematical methods of spatiotemporal analysis and to implement them in highquality modern software.Purpose. The purpose of this research is the development of information technology for trajectory data mining.Materials and Methods. Information technology contains the three main algorithms: revealing key pointsand sequences of interest with the use of density-based trajectories clustering of studied objects; detecting patterns of an object movement based on association rules and hierarchical cluster analysis of its motion trajectories in the time interval of observations, similarity measure of the motion trajectories has been proposed to be calculated on the basis of the DTW method with the use of the modified Haversine formula; new algorithm for revealing permanent routes and detecting groups of similar objects has been developed on the basis of clustering ensemblesof all studied trajectories in time. The clustering parameters are selected with multi-criteria quality evaluation.Results. The modern software that implements the proposed algorithms and provides a convenient interactionwith users and a variety of visualization tools has been created. The developed algorithms and software have beentested in detail on the artificial trajectories of moving objects and applied to analysis of real open databases.Conclusions. The experiments have confirmed the efficiency of the proposed information technology thatmay have a practicable application to trajectory data mining in various fields.

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The U.S. Inland Creel and Angler Survey Catalog (CreelCat): Development, Applications, and Opportunities

et al. 2021

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Inland recreational fishing, defined as primarily leisure‐driven fishing in freshwaters, is a popular pastime in the USA. State natural resource agencies endeavor to provide high‐quality and sustainable fishing opportunities for anglers. Managers often use creel and other angler survey data to inform state‐ and waterbody‐level management efforts. Despite the broad implementation of angler surveys and their importance to fisheries management at state scales, regional and national coordination among these activities is minimal, limiting data applicability for larger‐scale management practices and research. Here, we introduce the U.S. Inland Creel and Angler Survey Catalog (CreelCat), a first‐of‐its‐kind, publicly available national database of angler survey data that establishes a baseline of national inland recreational fishing metrics. We highlight research and management applications to help support sustainable inland recreational fishing practices, consider cautions, and make recommendations for implementation.

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Spatiotemporal Data Mining: Issues, Tasks And Applications

Abstract: ABSTRACT

Cited by 41 publications

References 38 publications

An Optimized User Behavior Prediction Model Using Genetic Algorithm on Mobile Web Structure

An Optimized User Behavior Prediction Model Using Genetic Algorithm on Mobile Web Structure

Information Technology for Trajectory Data Mining

The U.S. Inland Creel and Angler Survey Catalog (CreelCat): Development, Applications, and Opportunities

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