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Lecture Notes in Computer Science
Here we introduce a novel problem, that of addressing density-based queries in the spatio-temporal domain. ... We formally define a new class of density-based queries and give approximate, on-line techniques that answer them efficiently. ... CONCLUSIONS We addressed the problem of on-line discovery of dense areas in spatio-temporal environments. ...doi:10.1007/978-3-540-45072-6_18 fatcat:qty67r27lbgorn6jwvgdh4pcl4
Runes have angular shapes and lack horizontal lines because the primary storage medium was wood, although they may also be found on jewelry, tools, and weapons. ... The DB TECH REPORTS icon is made from two letters in an early version of the Rune alphabet, which was used by the Vikings, among others. ... Finding Dense Spatio-Temporal Areas Discovering dense areas is one of the most common topics for spatial and spatio-temporal data mining. ...doi:10.1109/mdm.2007.18 dblp:conf/mdm/GidofalviHP07 fatcat:lcpik3nzongpbfj3n2jnr3sjgm
In this paper, we study the problem of potential transmission cluster discovery based on the spatio-temporal logs. ... Leveraging two well-designed techniques of spatio-temporal compression and graph partition on bipartite contact graphs, our BCG-index approach achieves a good balance of index construction and online query ... In the following, we formulate the problem of potential cluster discovery on spatial-temporal database studied in this paper. ...doi:10.1145/3538492 fatcat:a7lpkinbxje4dj3tds6jiliwte
28th International Conference on Information Technology Interfaces, 2006.
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach to detect spatio-temporal outliers in large databases. ... In contrast to the existing outlier detection algorithms, the new algorithm has the ability of discovering outliers according to the non-spatial, spatial and temporal values of the objects. ... Introduction Spatio-temporal databases are growing very rapidly, both in size and in number. This condition results in an increasing need for knowledge discovery in spatio-temporal databases. ...doi:10.1109/iti.2006.1708474 fatcat:hsqxjyulk5ajdazoywmon7i324
Outlier detection is one of the major data mining methods. This paper proposes a three-step approach to detect spatio-temporal outliers in large databases. ... In contrast to the existing outlier detection algorithms, the new algorithm has the ability of discovering outliers according to the non-spatial, spatial and temporal values of the objects. ... Introduction Spatio-temporal databases are growing very rapidly, both in size and in number. This condition results in an increasing need for knowledge discovery in spatio-temporal databases. ...doi:10.2498/cit.2006.04.04 fatcat:cd67tm64kveupb54gwt6v755dy
In this paper, we present a knowledge discovery process applied to hydrological data. ... To achieve this objective, we combine successive methods to extract knowledge on data collected at stations located along several rivers. ... These techniques are the subject of the emerging field of Knowledge Discovery in Databases (KDD). ...dblp:conf/caise/Salas13 fatcat:r5joqwaq2vhdpheqisaeajumve
We study the discovery of spatio-temporal influence-based moving clusters in a database of spatiotemporal events. ... A spatio-temporal influence-based moving cluster is a sequence of spatial clusters, where each cluster is a set of nearby objects, such that each object in a cluster influences at least one object in the ... Research in Spatio-temporal cluster discovery or hotspot detection has been performed mostly in the field of epidemiology and crime analysis, where domain peoples are interested in identifying the dense ...doi:10.1145/2631926 fatcat:m32cnrlrtfg5fmxgqaczfgucuy
In this paper, we propose a novel technique, called DAD-MST, to detect dense areas based on the Maximum Spanning Tree (MST) algorithm applied over the communication antennas of a cell phone infrastructure ... The recent adoption of ubiquitous computing technologies (e.g. GPS, WLAN networks) has enabled capturing large amounts of spatio-temporal data about human motion. ... There are a variety of solutions for detecting dense areas in spatial  and spatio-temporal  ,  ,  domains. ...doi:10.1109/socialcom.2010.41 dblp:conf/socialcom/VieiraFOF10 fatcat:bmlxbeb4vngatk5uxpwc6ldidm
GPS devices allow recording the movement track of the moving object they are attached to. This data typically consists of a stream of spatio-temporal (x,y,t) points. ... These two kinds of experiments are reported in this paper. ... Work in this area focuses primarily on semantic models and trajectory knowledge discovery. ...doi:10.1145/1951365.1951398 dblp:conf/edbt/YanCPSA11 fatcat:d2v4jtbbxrdrrkkuymyjfwv26a
In this paper, we address the problem of mining spatio-temporal patterns from trajectory data. ... We provide a formal statement of efficient representation of spatio-temporal movements and propose a new approach to discover spatio-temporal patterns in trajectory data. ... In addition, to deliver the notion of temporal quantities into the pattern discovery, the mining process which discovers spatio-temporal regions should be modified. ...doi:10.3745/jips.2010.6.4.521 fatcat:pa7xxuep3zd7dbl4au52agem44
Proceedings of the 2009 SIAM Conference on "Mathematics for Industry"
The objective of the GeoPKDD (Geographic Privacy-aware Knowledge Discovery and Delivery), a project funded by European Commission under the Future and emerging technologies (FET) program of the 6th Framework ... Pursuing this ambitious objective, the GeoPKDD project has started a new exciting multidisciplinary research area, at the crossroads of mobility, data mining, and privacy. ... devices at a fine spatio-temporal resolution. ...doi:10.1137/1.9781611973303.2 fatcat:4ig3w67fbrbqvibvq3iwlw7qly
It transforms arbitrary data into spatio-temporal trajectories that can be analyzed only on the basis of their geometric relationships and characteristics. ... In an example, we illustrate how we can distinguish different types of users regarding temporal patterns and the learners' mobility. ... In this light we consider the current state of the Hypercube Database as a useful method for teachers and course administrators to examine students' behavior. ...doi:10.18420/in2017_171 dblp:conf/gi/FuchsH17 fatcat:cj22egod75aa3dzjjxdntrb3cu
Lecture Notes in Computer Science
A sketch of a case study on behavioral ecology is presented. ... Furthermore it is well suited to model trajectories of moving objects, which can be analysed by using inductive techniques, like clustering, in order to find common movement patterns. ... Spatio-temporal data mining is a subfield of data mining and knowledge discovery, aimed at the extraction of spatial and temporal patterns and relationships not explicitly contained in the database. ...doi:10.1007/11415763_7 fatcat:ypqwtgkylfcjhao54wuyut7xlu
For example, in the four oval regions shown on figure16, which basically include two or three dense area, corridors between the dense areas can be observed in line density map instead of point density ... Knowledge Discovery Traditional Knowledge Discovery Knowledge discovery is often used as a part in the acronym KDD (Knowledge Discovery from Databases), in this case, we are applying it to trajectory ...doi:10.1109/ramech.2008.4681321 dblp:conf/ram/Li08 fatcat:5rpvxkullzh55m4nvpdl6kccqi
in a large time series database. ... Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. ... Acknowledgments: This paper describes work undertaken in the context of the TagItSmart! project (www.tagitsmart.eu). TagItSmart! ...doi:10.3390/s17061427 pmid:28629156 pmcid:PMC5492522 fatcat:tnunvvciarho3dmdp5svywhtla
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