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Spatiotemporal Data Mining: A Computational Perspective
2015
ISPRS International Journal of Geo-Information
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Compared with other surveys in the literature, this paper emphasizes the statistical foundations of spatiotemporal data mining and provides comprehensive coverage of computational approaches for various ...
Explosive growth in geospatial and temporal data as well as the emergence of new technologies emphasize the need for automated discovery of spatiotemporal knowledge. ...
HM1582-08-1-0017 and HM0210-13-1-0005, and the University of Minnesota under OVPR U-Spatial. We would like to thank Kim Koffolt for the helpful comments in improving the readability of the paper. ...
doi:10.3390/ijgi4042306
fatcat:hwnwbw7wm5hx5c4ncrvv533qju
A general and parallel platform for mining co-movement patterns over large-scale trajectories
2016
Proceedings of the VLDB Endowment
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Discovering co-movement patterns from large-scale trajectory databases is an important mining task and has a wide spectrum of applications. ...
To the best of our knowledge, this is the first work to mine co-movement patterns in real life trajectory databases with hundreds of millions of points. ...
Acknowledgment: The authors would like to thank the anonymous reviewers for their responsible feedback. ...
doi:10.14778/3025111.3025114
fatcat:vrtqqjd42jfmbjq57lyz74cxzy
Big Data Analytics in Bioinformatics: A Machine Learning Perspective
[article]
2015
arXiv
pre-print
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However, there lack standard big data architectures and tools for many important bioinformatics problems, such as fast construction of co-expression and regulatory networks and salient module identification ...
Usually big data tools perform computation in batch-mode and are not optimized for iterative processing and high data dependency among operations. ...
ACKNOWLEDGMENTS The authors would like to thank the Ministry of HRD, Govt. of India for funding as a Centre of Excellence with thrust area in Machine Learning Research and Big Data Analytics for the period ...
arXiv:1506.05101v1
fatcat:oix7d5hecbfgthzhepznwyi6fm
29th International Conference on Data Engineering [book of abstracts]
2013
2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW)
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scalable Maximum Clique Computation Using Mapreduce Jingen Xiang, Cong Guo, Ashraf Aboulnaga (University of Waterloo) We present a scalable and fault-tolerant solution for the maximum clique problem based ...
constraints on movement patterns of the users, and the temporal and spatial resolution of the location exposure. ...
VolUnTeers ICDE-13 would like to extend our warm appreciation to our conference volunteers who assisted before, during and after the conference, to help make sure that everyone enjoys a great conference ...
doi:10.1109/icdew.2013.6547409
fatcat:wadzpuh3b5htli4mgb4jreoika
Cross-Covariance Models
[chapter]
2017
Encyclopedia of GIS
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Synonyms Cadaster; Land administration system; Land information system; Land policy; Land registry; Property register; Spatial reference frames ...
The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns. ...
Cross-References Indexing, Hilbert R-tree, Spatial Indexing, Multimedia Indexing The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the automated discovery ...
doi:10.1007/978-3-319-17885-1_100240
fatcat:2ojzb7es7rhofinw4abol6dgc4
Location Analytics for Location-Based Social Networks
[article]
2018
PhD series, Technical Faculty of IT and Design, ˜Aalborg=ålborgœ University
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Acknowledgements
Acknowledgements viii
Conclusion We proposed the problem of predicting future companions in LBSNs, and an efficient, nontrivial solution, COVER; this solution mines geo-social cohorts ...
For comparisons, we provide a baseline approach (BF) in which we mine the cohorts using a brute force way and two variants of a state-of-the-art approach, Group Finder [20] , i.e., GF-PAV and GF-PLM. ...
In particular, SpatialHadoop [5] , MongoDB [6] , and MD-base are mapreduce frameworks equipped with spatial features. ...
doi:10.5278/vbn.phd.tech.00038
fatcat:wwovvw4mnjbe5fqno7xn4qqo4e
Social networking data analysis tools & challenges
2018
Future generations computer systems
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The survey demonstrates challenges and future directions with a focus on text mining and the promising avenue of computational intelligence. ...
Though, both their recent advent and the fact that science is still in the frontiers of processing human-generated data, provokes the need for an update and comprehensible taxonomy of the related research ...
Events in the framework are represented as a 4-tuple <y, d, l, k>, where y stands for non-location named entities, d for a date, l for a location, and k for eventrelated keywords. ...
doi:10.1016/j.future.2016.10.019
fatcat:cqlp423pv5heplujb63qo7c6yq
Program book
2010
2010 IEEE 26th International Conference on Data Engineering Workshops (ICDEW 2010)
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TrajStore maintains an optimal index on the data and dynamically co-locates and compresses spatially and temporally adjacent segments on disk. ...
In particular, we aim to find a set of nearest co-located objects which together match the query tags. ...
when applied to social networks and searching for people, contacts or shared interests is very different from the search over documents studied in information retrieval. ...
doi:10.1109/icdew.2010.5452773
fatcat:oyq2tujbvjfpxjlyixux5q57vu
Point-of-Interest Recommendation
[chapter]
2017
Encyclopedia of GIS
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and insect feeding patterns for mosquito-borne diseases. ...
The models may range from descriptive, e.g. static estimates of correlations within large databases, to generative, e.g. computing the spread of disease via person-toperson interactions through a large ...
Arunasalam B, Chawla S, Sun P (2005, to
References
Cross-References Indexing, Hilbert R-Tree, Spatial Indexing, Multimedia Indexing ...
doi:10.1007/978-3-319-17885-1_100975
fatcat:myyebmb3hrhgnpqmobyyvm2xum
Distributed Gaussian Mixture Model Summarization Using the MapReduce Framework
[chapter]
2016
Lecture Notes in Computer Science
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The main purpose of the proposed method is to summarize a dataset with a density-based clustering algorithm called DBSCAN algorithm, and then summarize each discovered cluster using the SGMM approach in ...
In this thesis, this goal is achieved by proposing and implementing a distributed Gaussian Mixture Model Summarization using the MapReduce framework (MR-SGMM). ...
Further, mining large amounts of data for analysis of purchasing patterns, stock trends or client reviews could be an indispensable aid for business and marketing. ...
doi:10.1007/978-3-319-34111-8_39
fatcat:ykoufaup7fht7mmkrwuhihpzhq
The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools
[article]
2020
arXiv
pre-print
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Social network based applications have experienced exponential growth in recent years. ...
new metrics (termed degrees) in order to evaluate the different software tools and frameworks of SNA (a set of 20 SNA-software tools are analyzed and ranked following previous metrics). ...
In order to do that, Phillips et al. [290] presented a crime data analysis technique that allows for discovering co-distribution patterns between large, aggregated, heterogeneous datasets. ...
arXiv:2002.09485v1
fatcat:4b6fgh3lkvgn7cfx7mrwtyq24a
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators
[article]
2021
arXiv
pre-print
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Such an ability has strong implications in a wide variety of fields whose data is inherently relational, for which conventional neural networks do not perform well. ...
On the other hand, an in-depth analysis of current software and hardware acceleration schemes is provided, from which a hardware-software, graph-aware, and communication-centric vision for GNN accelerators ...
ACKNOWLEDGMENTS The authors would like to thank the anonymous reviewers and the editorial team for their constructive criticism, which has helped improve the quality of the paper. ...
arXiv:2010.00130v3
fatcat:u5bcmjodcfdh7pew4nssjemdba
Towards Disaster Resilient Smart Cities: Can Internet of Things and Big Data Analytics be the Game Changers?
2019
IEEE Access
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A variety of datasets (i.e., smart buildings, city pollution, traffic simulator, and twitter) are utilized for the validation and evaluation of the system to detect and generate alerts for a fire in a ...
The proposed architecture offers a generic solution for disaster management activities in smart city incentives. ...
Pattern recognition mechanism offers the machine learning ability to detect the useful patterns of information from textual or spatial data sets crucial for disaster management [48] . ...
doi:10.1109/access.2019.2928233
fatcat:37y7tmrs65dthjiezrtbzhrbve
A taxonomy and survey on Green Data Center Networks
2014
Future generations computer systems
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. • We present the state-of-the-art energy efficiency techniques for a DCN. • The survey elaborates on the DCN architectures (electrical, optical, and hybrid). • We also focus on traffic management, characterization ...
, and performance monitoring. • We present a comparative analysis of the aforementioned within the DCN domain. a b s t r a c t Data centers are growing exponentially (in number and size) to accommodate ...
The monitoring information is stored into a database for visualization, analysis, and mining. ...
doi:10.1016/j.future.2013.07.006
fatcat:f6btn5gljjetzphyg7w6lqa6jy
Tensors for Data Mining and Data Fusion
2016
ACM Transactions on Intelligent Systems and Technology
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, and from web mining to healthcare. ...
As a result, tensor decompositions, which extract useful latent information out of multiaspect data tensors, have witnessed increasing popularity and adoption by the data mining community. ...
Kolda for comments on earlier versions of this manuscript and identifying several additional references. The majority of this work was carried out while E. ...
doi:10.1145/2915921
fatcat:annpad5w2jcvnb4d3e5imiemlu
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