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Knowledge Discovery from Social Graph Data

Peter Braun, Alfredo Cuzzocrea, Carson K. Leung, Adam G.M. Pazdor, Kimberly Tran
2016 Procedia Computer Science  
In the current era of big data, many traditional data management and analytic approaches may not be suitable for handling the big data due to their well-known 5V's characteristics.  ...  In this paper, we present a knowledge-based system for social network analysis so as to support big data mining of interesting patterns from big social networks that are represented as graphs.  ...  Acknowledgment This project is partially supported by Natural Sciences and Engineering Research Council of Canada (NSERC) and the University of Manitoba.  ... 
doi:10.1016/j.procs.2016.08.250 fatcat:ngskvezw4vhkhgdnmjxezvueje

Community Detection Algorithms for Big Data using Graph Theory

2019 International journal of recent technology and engineering  
Community detection is a nowadays research problem in the Big Data era related to huge volume, variety, and velocity of data.  ...  This paper represents Big data in the form of graphs and detects community via some graph algorithms like METIS, Spectral Partitioning, hierarchical clustering, Markov Clustering, Genetic Algorithm based  ...  So Face book is a Big data example and in the Face book can be model as a graph and in the graph, we can also be used to find the communities.  ... 
doi:10.35940/ijrte.b1046.0982s1019 fatcat:z6seqywjgzesxhx3syxv7costm

Editorial for application-driven knowledge acquisition

Xue Li, Sen Wang, Bohan Li
2020 World wide web (Bussum)  
Information mining based on big data has brought about tremendous changes in many fields.  ...  and data mining.  ...  We would also like to thank the participants and attendees of the ADMA conference for the enlightening presentations and discussions.  ... 
doi:10.1007/s11280-020-00827-6 fatcat:gdt63za6mrewriu7frir2nhkby

Archaeology 4.0: Archaeology in the Third Era of Computing

Florian Thiery
2019 Zenodo  
semantic modelling and publication of Linked Data is reality, we end up in a knowledge era, in which the analysis and the creation of new knowledge through machines will be reality.  ...  Starting with an analogue era, in which research data was kept in books, followed by a digital era in which digitization progresses and data are published on the WWW, followed by a semantic era, in which  ...  Acknowledgements I would like to thank the Mainz Centre for Digitality in the Humanities and Cultural Studies (mainzed) and Römisch-Germanisches Zentralmuseum. In particular Prod. Dr.  ... 
doi:10.5281/zenodo.2629596 fatcat:6tvxbdlajnapnejk7g7xqh4epi

Archaeology 4.0: Archaeology in the Third Era of Computing

Florian Thiery
2019 Zenodo  
semantic modelling and publication of Linked Data is reality, we end up in a knowledge era, in which the analysis and the creation of new knowledge through machines will be reality.  ...  Starting with an analogue era, in which research data was kept in books, followed by a digital era in which digitization progresses and data are published on the WWW, followed by a semantic era, in which  ...  Acknowledgements I would like to thank the Mainz Centre for Digitality in the Humanities and Cultural Studies (mainzed) and Römisch-Germanisches Zentralmuseum. In particular Prof. Dr.  ... 
doi:10.5281/zenodo.2635487 fatcat:jzccyfprsbeotfptxh6edn54ey

Advances in big data programming, system software and HPC convergence

Ching-Hsien Hsu, Geoffrey Fox, Geyong Min, Sugam Sharma
2019 Journal of Supercomputing  
Automatically linking records from different data sources become more and more important in many big data applications.  ...  Big data applications In the era of big data, an increasing amount of image data is being generated on the Internet through daily social communication.  ... 
doi:10.1007/s11227-018-2706-x fatcat:ehkbtokau5henf324xukgfhgey

Graph Data: The Next Frontier in Big Data Modeling for Various Domains

Angira Amit Patel, Jyotindra Dharwa
2017 Indian Journal of Science and Technology  
Graph is considered as next frontier in the era of Big data due to its flexibility and self-explaining property.  ...  The prime objective of this research is to reveal graph database as an alternative of traditional relation database in the field of database.  ...  Graph Data Model for Bio-Chemical Data Graph data modeling and mining started primarily in practice for biological data like genome, protein structure and drug compounds.  ... 
doi:10.17485/ijst/2017/v10i21/112828 fatcat:7qprb6pdxrc3hpv4sk3olu4kmi

Preface of Special Issue on BigDataSE 2016

Heng Qi, Keqiu Li
2018 Computer systems science and engineering  
Acknowledgment This work is supported by the JSPS KAKENHI Grant Number JP16F16349.  ...  To address this issue, they propose an algorithm named TCRQDG, which can achieve fast and accurate query on large scale graph data. In the big data era, recommendation system is a very hot topic.  ...  However, the security of mobile devices need to be improved to deal with the malicious attacks in big data era.  ... 
doi:10.32604/csse.2018.33.057 fatcat:paq4x4asj5cq7gzb7fdr67lrta

Semantic Intelligence in Big Data Applications [article]

Valentina Janev
2021 arXiv   pre-print
The International Data Corporation also forecasts that more than 150B devices will be connected across the globe by 2025, most of which will be creating data in real-time, while 90 zettabytes of data will  ...  To leverage the potential of real data and build smart applications on top of sensory data, IoT-based systems integrate domain knowledge and context-relevant information.  ...  Acknowledgment The research presented in this paper is partly financed by the European Union (H2020 PLATOON, Pr. No: 872592; H2020 LAMBDA, Pr.  ... 
arXiv:2107.03853v1 fatcat:5odmdvcfd5ewrnfao5tyexpf2q

Business Intelligence and Analytics

Ee-Peng Lim, Hsinchun Chen, Guoqing Chen
2013 ACM Transactions on Management Information Systems  
In this article, we will categorize BIA research activities into three broad research directions: (a) big data analytics, (b) text analytics, and (c) network analytics.  ...  The article aims to review the state-of-the-art techniques and models and to summarize their use in BIA applications.  ...  To gain insights about consumer behavior in these graphs, we need to mine graphs or conduct graph-mining.  ... 
doi:10.1145/2407740.2407741 fatcat:enjlhfzqfnfqvlv63axun5dvee

Big Data Visualization Tools [article]

Nikos Bikakis
2018 arXiv   pre-print
Data visualization is the presentation of data in a pictorial or graphical format, and a data visualization tool is the software that generates this presentation.  ...  Data visualization provides users with intuitive means to interactively explore and analyze data, enabling them to effectively identify interesting patterns, infer correlations and causalities, and supports  ...  challenges that arise in the Big Data era.  ... 
arXiv:1801.08336v2 fatcat:n4kdbz6iyzbdrd2ycmh7uu7zle

Automatic Generalization of Residential Areas Based on "Paradigm" Theory and Big Data [chapter]

Tianlin Duo, Peng Zhang
2021 Advances in Transdisciplinary Engineering  
According to the key and difficult problems faced by residential area selection and simplification, residential area selection models and simplification models based on big data and deep learning are constructed  ...  Based on large-scale map data and deep learning technology, an automatic cartographic generalization problem-solving model is proposed in this paper.  ...  in the era of big data.  ... 
doi:10.3233/atde210244 fatcat:rtpzs3w5bvbhfgnadnhrmdwkge

Survey of Knowledge Graph Approaches and Applications

Hangjun Zhou, Tingting Shen, Xinglian Liu, Yurong Zhang, Peng Guo, Jianjun Zhang
2020 Journal on Artificial Intelligence  
With the advent of the era of big data, knowledge engineering has received extensive attention. How to extract useful knowledge from massive data is the key to big data analysis.  ...  Finally, the future development direction and challenges of the knowledge graph are prospected.  ...  First of all, although the era of big data has produced a large amount of data, but the release of data is not standardized, and the data quality is not high, so it is necessary to mine high-quality data  ... 
doi:10.32604/jai.2020.09968 fatcat:yvggvqhexze43jyomytsf7kfr4

A conversation with Professor Li-Zhu Zhou

Li-Zhu Zhou
2012 SIGKDD Explorations  
Now we are in an era of Big Data and are suffering from the data deluge problems brought by the explosion of such huge amount of data.  ...  In the graph data mining research topic, we mainly investigate the problems such as coherent sub-graph mining and graph generator mining for classification.  ... 
doi:10.1145/2207243.2207267 fatcat:e75jccv6oze2vos6hm7fxdkici

Mining big data

Wei Fan, Albert Bifet
2013 SIGKDD Explorations  
We introduce four articles, written by influential scientists in the field, covering the most interesting and state-of-the-art topics on Big Data mining.  ...  Big Data is a new term used to identify the datasets that due to their large size and complexity, we can not manage them with our current methodologies or data mining software tools.  ...  ACKNOWLEDGEMENTS We would like to thank Jimmy Lin, Dmitriy Ryaboy, Jiawei Han, Yizhou Sun, U Kang, Christos Faloutsos and Xavier Amatriain for contributing to this special section.  ... 
doi:10.1145/2481244.2481246 fatcat:4desfvwbqrfhpgez4cm7wwxwtu
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