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Interactive Probabilistic Post-Mining of User-Preferred Spatial Co-Location Patterns
2018
2018 IEEE 34th International Conference on Data Engineering (ICDE)
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Spatial co-location pattern mining is an important task in spatial data mining. ...
A probabilistic model is further introduced to measure the user feedback-based subjective preferences on resultant co-location patterns. ...
INTRODUCTION The extraction of spatial co-location patterns is a rising and promising field in spatial data mining. ...
doi:10.1109/icde.2018.00124
dblp:conf/icde/WangBC18
fatcat:rwm4grjp7nf65mkdaoetfaxojm
Multi-Resolution Pruning Based Co-Location Identification In Spatial Data
2014
IOSR Journal of Computer Engineering
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A co-location spatial pattern is a pattern of multiple groups which co-relates spatial features or events that are frequently located in same zone. ...
Co-location pattern mining emphasizes overall analysis by manipulating the proportion of spatial features and other relevant information's. ...
Pattern mining is data mining method that find existing pattern in data .A spatial co-location pattern is a pattern which represents a subset of spatial features whose instance frequently located in close ...
doi:10.9790/0661-16260105
fatcat:bfwldlagnfcpppndfs64cy4apu
Mining Spatial Co-location Patterns with Dynamic Neighborhood Constraint
[chapter]
2009
Lecture Notes in Computer Science
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Spatial co-location pattern mining is an interesting and important issue in spatial data mining area which discovers the subsets of features whose events are frequently located together in geographic space ...
Based on this, we define the mining task as an optimization problem and propose a greedy algorithm for mining co-location patterns with dynamic neighborhood constraint. ...
Introduction Spatial co-location pattern mining [1] is an interesting and important issue in spatial data mining area which discovers the subsets of features (co-locations) whose events are frequently ...
doi:10.1007/978-3-642-04174-7_16
fatcat:7syesrycsrcetptjzynxlnffpq
Zonal Co-location Pattern Discovery with Dynamic Parameters
2007
Seventh IEEE International Conference on Data Mining (ICDM 2007)
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Previous studies have focused on discovering global spatial co-location patterns with a fixed interest measure threshold. ...
Discovering zonal spatial co-location patterns is an important problem with many applications in areas such as ecology, public health, and homeland defense. ...
Related Work: Previous research on spatial co-location pattern mining has focused on discovering global colocation patterns based on a fixed interest measure. ...
doi:10.1109/icdm.2007.102
dblp:conf/icdm/CelikKS07
fatcat:sdphuwpmb5fglkp2tzul5zsosm
CONNEKT: Co-Located Nearest Neighbor Search using KNN Querying with K-D Tree
2019
International journal of recent technology and engineering
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One such application is to use co-location pattern mining for a context aware based search. ...
Instances of various spatial features that are closely found together are called as spatial co-located patterns. ...
The mined co-located patterns got as output from the co-location pattern mining algorithm will be in the form of doublets, triplets, etc. based upon the pattern size. ...
doi:10.35940/ijrte.b1741.078219
fatcat:ebqamcboxvdijlja5t5lutz5xi
Guest editorial: special issue on Web data querying, mining, and privacy preserving
2019
World wide web (Bussum)
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The authors develop a novel and efficient mechanism to solve the problem, including a quad-tree based indexing structure, indexing update technique, and a best-first based searching algorithm. ...
The first paper studies the topic of querying web data, while the next two papers investigates the topic of mining on web data. ...
The second paper "Mining Maximal Sub-Prevalent Co-location Patterns" by Lizhen Wang, Xuguang Bao, Lihua Zhou, and Hongmei Chen explores the problem of spatial prevalent colocation pattern mining to discover ...
doi:10.1007/s11280-019-00690-0
fatcat:5y2aymc325futk6bf3634edp6e
An Improved Approximation Algorithm for Co-location Mining in Uncertain Data Sets using Probabilistic Approach
2017
APTIKOM Journal on Computer Science and Information Technologies
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In this paper we investigate colocation mining problem in the context of uncertain data. Uncertain data is a partially complete data. ...
Handling such data is a challenge for knowledge discovery particularly in colocation mining. One straightforward method is to find the Probabilistic Prevalent colocations (PPCs). ...
For this we discuss the co-location pattern mining over spatial data sets. Many important applications use colocation mining. For example: 1. ...
doi:10.11591/aptikom.j.csit.91
fatcat:336snv76cjckpaoxf3mmj2bppm
An Improved Approximation Algorithm for Co-location Mining in Uncertain Data Sets using Probabilistic Approach
2020
APTIKOM Journal on Computer Science and Information Technologies
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The experimental results on the selected dataset show the significant improvement in computational time in comparison to some of the existing methods used incolocation mining. ...
For this we discuss the co-location pattern mining over spatial data sets. Many important applications use colocation mining. For example: 1. ...
. , } ISSN: 2528-2417
An Improved Approximation Algorithm for Co-location Mining in… (M. ...
doi:10.34306/csit.v2i1.61
fatcat:a5furaxtcfbj7nqu4gswnnsy7i
Identifying patterns in spatial information: A survey of methods
2011
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
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Spatial data mining tasks, explains in detail four main output patterns and methods of SDM related to anomalies, clustering, co-location, and prediction. ...
In order to deal with this, spatial statistics has explored several corrections to characterize the statistical significance of spatial outliers. 67
Co-location Patterns Co-location patterns represent ...
doi:10.1002/widm.25
fatcat:xqcn7cf5bnbevlm2xlhvpr2gle
Regional co-location pattern scoping on a street network considering distance decay effects of spatial interaction
2017
PLoS ONE
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Regional co-location scoping intends to identify local regions where spatial features of interest are frequently located together. ...
by calculating the co-location prevalence measure values, which are based on the density variation between different features. ...
This process is usually realized via spatial co-location/correlation pattern mining [1] [2] [3] . ...
doi:10.1371/journal.pone.0181959
pmid:28763496
pmcid:PMC5538746
fatcat:mf7p6lssljcoff47alfzbvms4i
Discovering co-location patterns with aggregated spatial transactions and dependency rules
2017
International Journal of Data Science and Analytics
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Co-location pattern mining focuses on finding associations among spatial features. ...
Existing co-location pattern mining techniques mainly rely on frequency based thresholds which discard the rare patterns and find the noisy patterns. ...
We originally outlined the aforementioned problem and proposed algorithms to mine spatial contrast and common sets in [1] using a GT-based co-location pattern mining method. ...
doi:10.1007/s41060-017-0079-5
dblp:journals/ijdsa/JabbarBZO18
fatcat:dsqwtkvllzdt7po4jrs3h4kgra
A Novel Filtered Based Grid partitioning multiple reducers skyline computation using Hadoop framework
2018
International Journal of Engineering & Technology
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Another major limitation with the sequential spatial pattern mining models is that a large number of spatial candidate sets are generated with duplicate event sets. ...
In this model, a filtered based k-nearest neighbor approach is used to eliminate the sparsity or empty patterns using the hadoop framework. ...
Here, they identified all issues of spatial co-location mining patterns with rare events. ...
doi:10.14419/ijet.v7i2.7.10923
fatcat:sx5lgrifajerdjv3h57pwqonbe
Geo-Social Co-location Mining
2015
Second International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data - GeoRich'15
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This work introduces geo-social co-location mining, the problem of finding social groups that are frequently found at the same location. ...
The second sub-problem of mining the resulting probabilistic co-location instances requires efficient for large databases having a high degree of uncertainty. ...
Spatial co-location patterns may yield important insights for many applications. ...
doi:10.1145/2786006.2786010
dblp:conf/sigmod/WeilerSMR15
fatcat:nqf3glfrtjcrlfinsp3axceefe
Spatio–temporal Rule Mining: Issues and Techniques
[chapter]
2005
Lecture Notes in Computer Science
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Recent advances in communication and information technology, such as the increasing accuracy of GPS technology and the miniaturization of wireless communication devices pave the road for Location-Based ...
To achieve high quality for such services, spatiotemporal data mining techniques are needed. In this paper, we describe experiences with spatio-temporal rule mining in a Danish data mining company. ...
A single generic scenario may be envisioned for these location-based services. ...
doi:10.1007/11546849_27
fatcat:dgv5twqqyre4zkuq2gmxyzr7rm
Mining spatiotemporal video patterns towards robust action retrieval
2013
Neurocomputing
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An APrior based frequent itemset mining scheme is then deployed over the spatiotemporal co-located words to discover co-location video patterns. ...
In this paper, we present a spatiotemporal co-location video pattern mining approach with application to robust action retrieval in YouTube videos. ...
Fig. 1 . 1 The proposed co-location video pattern mining based action search framework. ...
doi:10.1016/j.neucom.2012.06.044
fatcat:x5bnf6no6bgdfgzrvxypqghqlm
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