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Spatiotemporal event sequence discovery without thresholds

Berkay Aydin, Soukaina Filali Boubrahimi, Ahmet Kucuk, Bita Nezamdoust, Rafal A. Angryk
2020 Geoinformatica  
Spatiotemporal event sequences (STESs) are the ordered series of event types whose instances frequently follow each other in time and are located close-by.  ...  The quality of the discovered sequences is of great importance to the domain experts who use these algorithms. We introduce a novel algorithm to find the most relevant STESs without threshold values.  ...  Conclusion and future work In this work, we have introduced a novel spatiotemporal event sequence mining algorithm -RAND-ESMINER, specifically designed for discovering STESs without user-defined thresholds  ... 
doi:10.1007/s10707-020-00427-6 pmid:33192166 pmcid:PMC7649715 fatcat:uvsaaqyw2zclpmahml4owu2xee

Discovering spatiotemporal event sequences

Berkay Aydin, Rafal Angryk
2016 Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems - MobiGIS '16  
Spatiotemporal event sequences are the series of event types whose trajectory-based instances follow each other in spatiotemporal context.  ...  In this thesis, we will focus on discovering spatiotemporal event sequences from large-scale region trajectory datasetes with event annotations.  ...  Bootstrap Approach: Mining Spatiotemporal Event Sequences without Thresholds Bootstrap is a resampling technique for estimating the distribution of a statistic [149] , and it is especially useful when  ... 
doi:10.1145/3004725.3004735 fatcat:3m7tehj3yjawdg2htdvuwn6guu

Concealing Sequential and Spatiotemporal patterns using Polynomial Sanitization

A. Vijay, M H M Krishna Prasad
2013 International Journal of Computer Applications  
A polynomial sanitization algorithm was adopted and implemented over the spatiotemporal patterns extracted from moving objects databases.  ...  That is, it may example, sensitive sequences. At the end HHA needs to compute thresholds for each event in every sequence.  ...  disclosure threshold.  ... 
doi:10.5120/11603-6970 fatcat:joyl7eknkrbabefde7urxmkdbu

Discovering Tight Space-Time Sequences [chapter]

Riccardo Campisano, Heraldo Borges, Fabio Porto, Fabio Perosi, Esther Pacitti, Florent Masseglia, Eduardo Ogasawara
2018 Lecture Notes in Computer Science  
The problem of discovering spatiotemporal sequential patterns affects a broad range of applications. Many initiatives find sequences constrained by space and time.  ...  The discovery of such patterns along with their constraints may lead to extract valuable knowledge that can remain hidden using traditional methods since their support is extremely low over the entire  ...  An event may be classified as an occurrence of a phenomenon in a given space and time. A spatiotemporal sequential pattern is a sequence of events that are constrained in space and time [8] .  ... 
doi:10.1007/978-3-319-98539-8_19 fatcat:i5bwfpowm5ddfh7a2qtkkvuauy

Spatiotemporal correlations of aftershock sequences

Tiago P. Peixoto, Katharina Doblhoff-Dier, Jörn Davidsen
2010 Journal of Geophysical Research  
Here, we study the spatiotemporal correlations of two aftershock sequences form California (Parkfield and Hector Mine) using the recently introduced concept of "recurrent" events.  ...  While they are typically identified with periods of enhanced seismic activity after a large earthquake as characterized by the Omori law, our knowledge of the spatiotemporal correlations between events  ...  on the actual history of events without any further assumptions .  ... 
doi:10.1029/2010jb007626 fatcat:as4azo3vm5ggdoyjd4lfaiidg4

A Unifying Framework for Analysis of Spatial-Temporal Event Sequence Similarity and Its Applications

Fuyu Xu, Kate Beard
2021 ISPRS International Journal of Geo-Information  
This unified representation of spatiotemporal event sequences (STES) supports different event data types and provides support for data mining and sequence classification and clustering.  ...  We present a framework for a novel matrix-based spatiotemporal event sequence representation that unifies punctual and interval-based representation of events.  ...  pattern discovery.  ... 
doi:10.3390/ijgi10090594 fatcat:55h7xtjrinabretxww72gsoyxm

Extracting spatiotemporal human activity patterns in assisted living using a home sensor network

Dimitrios Lymberopoulos, Athanasios Bamis, Andreas Savvides
2008 Proceedings of the 1st ACM international conference on PErvasive Technologies Related to Assistive Environments - PETRA '08  
Using this stream of symbols, we formulate the problem of human activity modeling as a spatiotemporal pattern-matching problem on top of the sequence of symbolic information the sensor network produces  ...  The sensor network is modeled as a source of spatiotemporal symbols whose output is triggered by the monitored person's motion over space and time.  ...  There, the notion of frequent itemset and frequent sequential pattern discovery in a sequence of events is introduced.  ... 
doi:10.1145/1389586.1389621 dblp:conf/petra/LymberopoulosBS08 fatcat:rm3ap24l55fnlbfzfbhmjgq6je

Extracting spatiotemporal human activity patterns in assisted living using a home sensor network

Dimitrios Lymberopoulos, Athanasios Bamis, Andreas Savvides
2010 Universal Access in the Information Society  
Using this stream of symbols, we formulate the problem of human activity modeling as a spatiotemporal pattern-matching problem on top of the sequence of symbolic information the sensor network produces  ...  The sensor network is modeled as a source of spatiotemporal symbols whose output is triggered by the monitored person's motion over space and time.  ...  There, the notion of frequent itemset and frequent sequential pattern discovery in a sequence of events is introduced.  ... 
doi:10.1007/s10209-010-0197-5 fatcat:ulh6elwqgrgevooqyj2aqh4f2e

Computer vision tracking of stemness

Kang Li, Eric D. Miller, Mei Chen, Takeo Kanade, Lee E. Weiss, Phil G. Campbell
2008 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
In particular, we present a machine-learning approach for detecting spatiotemporal mitosis events without image segmentation.  ...  We consider mitoses as spatiotemporal event patterns, and aim to detect them in any spatiotemporal volumes of appropriate scales in the image sequence.  ...  Fig. 4 . 4 Result of spatiotemporal mitosis event detection for an entire sequence (left), and in one frame (right).  ... 
doi:10.1109/isbi.2008.4541129 dblp:conf/isbi/LiMCKWC08 fatcat:dp73z5cgyjbzdkzim27ta4jalq

Spatiotemporal Data Mining: Issues, Tasks And Applications

Venkateswara Rao K
2012 International Journal of Computer Science & Engineering Survey  
Spatiotemporal data usually contain the states of an object, an event or a position in space over a period of time.  ...  System functional requirements for such kind of knowledge discovery and database structure are discussed. Finally applications of spatiotemporal data mining are presented.  ...  Cascading Spatiotemporal Pattern discovery Cascading spatiotemporal patterns discovery [37] from a Boolean spatiotemporal event types data set uncovers partially ordered subsets of event types whose  ... 
doi:10.5121/ijcses.2012.3104 fatcat:smom5x2ybbgilavylsg7dju3pu

Efficient Mining of Spatiotemporal Patterns [chapter]

IIias Tsoukatos, Dimitrios Gunopulos
2001 Lecture Notes in Computer Science  
The problem of mining spatiotemporal patterns is finding sequences of events that occur frequently in spatiotemporal datasets. Spatiotemporal datasets store the evolution of objects over time.  ...  The discovered patterns are sequences of events that occur most frequently.  ...  A specific spatiotemporal event is a spatiotemporal itemset IS associated with some location Lid j and some point in time t k .  ... 
doi:10.1007/3-540-47724-1_22 fatcat:bhfxr2k355avdlm2in5jiqhrue

Foreshock and Aftershocks in Simple Earthquake Models

J. Kazemian, K. F. Tiampo, W. Klein, R. Dominguez
2015 Physical Review Letters  
If spatial heterogeneity affects the 1 spatiotemporal behavior of earthquake sequences, including earthquake return period and 2 precursory activity (foreshocks), then it should be possible to link stress  ...  The smaller stochastic, GR scaling events which result from the triggering 10 process have a small impact on the event statistics due to the large separation of failure 11 thresholds.  ... 
doi:10.1103/physrevlett.114.088501 pmid:25768785 fatcat:7zwrxjis5vhl5nqaxzp3tiaacq

Mining Frequent Trajectory Patterns from GPS Tracks

Gang Chen, Baoquan Chen, Yizhou Yu
2010 2010 International Conference on Computational Intelligence and Software Engineering  
Second, each trajectory is a long spatiotemporal sequence, without any predefined segmentation contributing to a pattern.  ...  ε , a similarity threshold η , and support threshold min_sup .  ... 
doi:10.1109/cise.2010.5677000 fatcat:ttzqtfatwjfqhi3gpxt5e7up7y

REAL-TIME GIS AND ITS APPLICATION IN INDOOR FIRE DISASTER

W. Xu, Q. Zhu, Y. Zhang, Y. Ding, M. Hu
2013 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The paper proposes a spatiotemporal changeoriented three-domain model with the emphasis on the semantic interaction relationship of object, event and process.  ...  Based on this model, a semantic enrichment method for multi-scale spatiotemporal change is put forward.  ...  The common spatiotemporal hierarchy like "Event-Process-State" and "Event-Process-Sequence-Region" just extract simple processes from discrete temporal information and group them as an event (Yuan, 2001  ... 
doi:10.5194/isprsarchives-xl-2-w2-121-2013 fatcat:ktsantukvvevvhu3uat6o55nbq

Spatiotemporal Neighborhood Discovery for Sensor Data [chapter]

Michael P. McGuire, Vandana P. Janeja, Aryya Gangopadhyay
2010 Lecture Notes in Computer Science  
The purpose of the spatiotemporal neighborhoods is to provide regions in the data where knowledge discovery tasks such as outlier detection, can be focused.  ...  ABSTRACT The focus of this paper is the discovery of spatiotemporal neighborhoods in sensor datasets where a time series of data is collected at many spatial locations.  ...  EXPERIMENTAL RESULTS Our experimental results are organized as follows: • Spatial Neighborhood discovery • Temporal Interval discoverySpatiotemporal Neighborhood discovery We utilized two datasets Sea  ... 
doi:10.1007/978-3-642-12519-5_12 fatcat:bu7aenettjbpfku5vzuk2nzmum
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