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Spatiotemporal Data Mining: A Computational Perspective

Shashi Shekhar, Zhe Jiang, Reem Ali, Emre Eftelioglu, Xun Tang, Venkata Gunturi, Xun Zhou
2015 ISPRS International Journal of Geo-Information  
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

Qi Fan, Dongxiang Zhang, Huayu Wu, Kian-Lee Tan
2016 Proceedings of the VLDB Endowment  
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]

Hirak Kashyap, Hasin Afzal Ahmed, Nazrul Hoque, Swarup Roy, Dhruba Kumar Bhattacharyya
2015 arXiv   pre-print
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)  
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  
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]

Muhammad Aamir Saleem
2018 PhD series, Technical Faculty of IT and Design, ˜Aalborg=ålborgœ University  
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/ fatcat:wwovvw4mnjbe5fqno7xn4qqo4e

Social networking data analysis tools & challenges

Androniki Sapountzi, Kostas E. Psannis
2018 Future generations computer systems  
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)  
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  
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]

Arina Esmaeilpour, Elnaz Bigdeli, Fatemeh Cheraghchi, Bijan Raahemi, Behrouz H. Far
2016 Lecture Notes in Computer Science  
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]

David Camacho, Àngel Panizo-LLedot, Gema Bello-Orgaz, Antonio Gonzalez-Pardo, Erik Cambria
2020 arXiv   pre-print
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]

Sergi Abadal, Akshay Jain, Robert Guirado, Jorge López-Alonso, Eduard Alarcón
2021 arXiv   pre-print
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?

Syed Attique Shah, Dursun Zafer Seker, M.Mazhar Rathore, Sufian Hameed, Sadok Ben Yahia, Dirk Draheim
2019 IEEE Access  
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

Kashif Bilal, Saif Ur Rehman Malik, Osman Khalid, Abdul Hameed, Enrique Alvarez, Vidura Wijaysekara, Rizwana Irfan, Sarjan Shrestha, Debjyoti Dwivedy, Mazhar Ali, Usman Shahid Khan, Assad Abbas (+2 others)
2014 Future generations computer systems  
. • 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

Evangelos E. Papalexakis, Christos Faloutsos, Nicholas D. Sidiropoulos
2016 ACM Transactions on Intelligent Systems and Technology  
, 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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