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Processes Meet Big Data: Scaling Process Discovery Algorithms in Big Data Environment

Reguieg Hicham, Benallal Mohamed Anis
2021 Journal of King Saud University: Computer and Information Sciences  
To cope with this issue, we propose a distributed implementation, based on Spark framework, of the alpha and heuristic algorithms to support efficient scalable process discovery for big process data.  ...  However, the performance of these techniques is limited when dealing with Big Data.  ...  ., 2010) ), many researches interested in combining big data research area and process analysis. The first study that incorporates MapReduce with process mining was in (Reguieg et al., 2012) .  ... 
doi:10.1016/j.jksuci.2021.02.008 fatcat:dvebvy7plvf2zfx3swtxrikigm

Business Process Mining [article]

Asef Pourmasoumi, Ebrahim Bagheri
2016 arXiv   pre-print
One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization.  ...  The aim of process mining is to extract knowledge from event logs of today's organizational information systems.  ...  The idea of the Alpha algorithm is simple and used by many process mining algorithms. The α-algorithm scans the event log for particular patterns.  ... 
arXiv:1607.00607v1 fatcat:3mndidjjnrdvjcfh4hvzv7zup4

Comprehensive Analysis Of Data Mining Tools

S. Sarumathi, N. Shanthi
2015 Zenodo  
Due to the fast and flawless technological innovation there is a tremendous amount of data dumping all over the world in every domain such as Pattern Recognition, Machine Learning, Spatial Data Mining,  ...  In this survey the diverse tools are illustrated with their extensive technical paradigm, outstanding graphical interface and inbuilt multipath algorithms in which it is very useful for handling significant  ...  Hadoop is not prepared with sophisticated machine learning algorithms as the majority of the algorithms do not fit its Map Reduce paradigm.  ... 
doi:10.5281/zenodo.1109306 fatcat:rser2mblkzfwdcbi2xdqtpcrae

Process mining using BPMN

Anna A. Kalenkova, Wil M. P. van der Aalst, Irina A. Lomazova, Vladimir A. Rubin
2016 Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems - MODELS '16  
The representational bias (a way to model processes) plays an important role in process mining.  ...  Ulrich Frank. tive can be integrated with data and resource perspectives discovered from event logs.  ...  The interest in Data Science and Big Data signifies the growing importance of evidence-based approaches.  ... 
doi:10.1145/2976767.2987688 fatcat:bpwfjqxavnbq5mbeqm2bsjm7oa

Genetic Process Mining [chapter]

W. M. P. van der Aalst, A. K. Alves de Medeiros, A. J. M. M. Weijters
2005 Lecture Notes in Computer Science  
This second extension is implemented as the Alpha++ algorithm plug-in in the ProM framework.  ...  All algorithms are implemented in the DaGama tool that is part of the data analysis framework Balboa. In [23, 26] , Cook et al. extend their Markov approach to mine concurrent process models.  ... 
doi:10.1007/11494744_5 fatcat:5or5zabuave2vpftpvdqfbiwvy

Scalable parallel data mining for association rules

Eui-Hong Han, George Karypis, Vipin Kumar
1997 Proceedings of the 1997 ACM SIGMOD international conference on Management of data - SIGMOD '97  
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items.  ...  In this paper, we present two new parallel algorithms for mining association rules.  ...  The communication and idling overheads were reduced using a better data movement communication mechanism, and redundant work was reduced by partitioning the candidate set intelligently and using bit maps  ... 
doi:10.1145/253260.253330 dblp:conf/sigmod/HanKK97 fatcat:ezklpuxuivarfdqvi2mu3vsfbi

Scalable parallel data mining for association rules

Eui-Hong Han, G. Karypis, V. Kumar
2000 IEEE Transactions on Knowledge and Data Engineering  
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items.  ...  In this paper, we present two new parallel algorithms for mining association rules.  ...  The communication and idling overheads were reduced using a better data movement communication mechanism, and redundant work was reduced by partitioning the candidate set intelligently and using bit maps  ... 
doi:10.1109/69.846289 fatcat:eiccyoyegffi7luooucn3dsas4

Scalable parallel data mining for association rules

Eui-Hong Han, George Karypis, Vipin Kumar
1997 SIGMOD record  
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items.  ...  In this paper, we present two new parallel algorithms for mining association rules.  ...  The communication and idling overheads were reduced using a better data movement communication mechanism, and redundant work was reduced by partitioning the candidate set intelligently and using bit maps  ... 
doi:10.1145/253262.253330 fatcat:f57qlkwkxfgdfhcxmb4imlb5li

Scaling data mining in massively parallel dataflow systems

Sebastian Schelter
2014 Proceedings of the 2014 SIGMOD PhD symposium on - SIGMOD'14 PhD Symposium  
the modern "Big Data" revolution.  ...  Once a map worker finishes processing an input split, it reports this progress to the master, which notifies the reduce workers.  ... 
doi:10.1145/2602622.2602631 dblp:conf/sigmod/Schelter14 fatcat:kejcowbahrfl7mguzivnolwtoq

Text Mining for Drug–Drug Interaction [chapter]

Heng-Yi Wu, Chien-Wei Chiang, Lang Li
2014 Msphere  
DDI text mining tools for PK data collection from the literature and data integration from multiple databases.  ...  Biomedical Text Mining-Text mining refers to the process of deriving highquality information from text, which relies on NLP.  ...  DDI Text Mining We implemented the approach described by [37] for the DDI extraction.  ... 
doi:10.1007/978-1-4939-0709-0_4 pmid:24788261 pmcid:PMC4636907 fatcat:jdxhh37g2zer3n4gikt34ewkry

Entrepreneurial Process [chapter]

2018 Encyclopedia of Social Network Analysis and Mining  
The multi-frame MAP algorithm spends nearly 90 percent of its processing time on MAD.  ...  Since the HRVS algorithm works with video data, it is no surprise that it was not completely straightforward to implement HRVS using PIPT.  ...  A.3.3 Parallel Visualization The parallel visualization toolkit (PVIZ) is an interface between the PIPT and Sun's Xil foundation image processing library.  ... 
doi:10.1007/978-1-4939-7131-2_100334 fatcat:hovad5v2gzgipk2ga36pvwaj6y

Process mining in healthcare: a systematised literature review

Mahdi Ghasemi, Daniel Amyot
2016 International Journal of Electronic Healthcare  
Section 5 focuses on process mining in healthcare, with its main contributions categorised and summarised. Section 6 discusses several threats to the validity of the reviews, including this one.  ...  One domain amenable to process mining is healthcare, where an enormous amount of data is generated by care processes, but where realistic care models are seldom available.  ...  In the second strategy, a new process mining technique or algorithm with an objective particular to each specific case study is implemented.  ... 
doi:10.1504/ijeh.2016.078745 fatcat:dnyvrgo7gjbq7adikoz3mxokga

Process mining using BPMN: relating event logs and process models

Anna A. Kalenkova, Wil M. P. van der Aalst, Irina A. Lomazova, Vladimir A. Rubin
2015 Journal of Software and Systems Modeling  
The representational bias (a way to model processes) plays an important role in process mining.  ...  Ulrich Frank. tive can be integrated with data and resource perspectives discovered from event logs.  ...  The interest in Data Science and Big Data signifies the growing importance of evidence-based approaches.  ... 
doi:10.1007/s10270-015-0502-0 fatcat:k4diwj2rovftzgyqlqt33vrlqm

Mining Unstructured Software Repositories [chapter]

Stephen W. Thomas, Ahmed E. Hassan, Dorothea Blostein
2013 Evolving Software Systems  
However, data in many software repositories is currently unused because the data is unstructured, and therefore difficult to mine and analyze.  ...  M INING SOFTWARE REPOSITORIES, which is the process of analyzing the data related to software development practices, is an emerging field which aims to aid development teams in their day to day tasks.  ...  However, in its raw, unparsed form, the text is simply a collection of characters with no structure and no meaning to a data mining algorithm.  ... 
doi:10.1007/978-3-642-45398-4_5 fatcat:n5ivswn6brfupjbsuomwddokd4

An Electrical Mine Monitoring System Utilizing the IEC 61850 Standard

David C. Mazur, Joseph Sottile, Thomas Novak
2015 IEEE transactions on industry applications  
ii) command and control methods for communication based assisted automation of IEDs for mining firms, (iii) effective solutions to incorporate electrical distribution data in the process control system  ...  This dissertation investigated the steps involved in interfacing IEDs to a mining process control network via the use of the IEC 61850 standard.  ...  Mapping Example The following example was created to illustrate how data, Alpha-Hotel, is packaged and mapped in the gateway module.  ... 
doi:10.1109/tia.2014.2339403 fatcat:46ggknyolffklpuj5enepixrge
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