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JGetMove: Mining Multiple Movement Patterns

Abstract : Recent improvements in positioning technology have led to a much wider availability of massive moving object data. A crucial task is to find the moving ob jects that travel together. Usually, these ob ject sets are called object movement patterns. Due to the emergence of many different kinds of object movement patterns in recent years, different approaches have been proposed to extract them. However, each approach only focuses on mining a specific kind of patterns. In addition to being a painstak- ing task due to the large number of algorithms used to mine and manage patterns, it is also time consuming. Moreover, we have to execute these al- gorithms again whenever new data are added to the existing database. To address these issues, we first redefine movement patterns in the itemset context. Secondly, we propose a unifying approach, named GeTMove, which uses a frequent closed itemset-based object movement pattern-mining algorithm to mine and manage different patterns. This code is a Java implementation of GetMove called JGetMove. The description of the approach is available at : Nhathai Phan, Pascal Poncelet, Maguelonne Teisseire. All in One: Mining Multiple Movement Pat- terns. International Journal of Information Technology and Decision Making, World Scientific Pub- lishing, 2016, 15 (5), pp.1115-1156.
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Present sur SoftwareHeritage - Identifier : swh:1:dir:3aa04f1229ee15494a1cd20fe893a37c0faad148;origin=https://hal.archives-ouvertes.fr/lirmm-02137577;visit=swh:1:snp:727e23feecdd43afc0ae5309639c85aa71a7ae2a;anchor=swh:1:rev:0d231f616df7c5e55d8b30d2a24c52e126a0b8b0;path=/  Browse

https://hal-lirmm.ccsd.cnrs.fr/lirmm-02137577
Contributor : Pascal Poncelet <>
Submitted on : Thursday, May 23, 2019 - 10:32:24 AM
Last modification on : Thursday, July 2, 2020 - 1:57:43 PM

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