Filters








7 Hits in 2.8 sec

DB-XES: Enabling Process Discovery in the Large [chapter]

Alifah Syamsiyah, Boudewijn F. van Dongen, Wil M. P. van der Aalst
2018 Lecture Notes in Business Information Processing  
To this end, we first introduce DB-XES as a database schema which resembles the standard XES structure, we provide a transparent way to access event data stored in DB-XES, and we show how this greatly  ...  Current process discovery techniques are able to efficiently handle imported event log files that fit in the computer's memory.  ...  Given the abundance of event data, the challenge is to enable process mining in the large.  ... 
doi:10.1007/978-3-319-74161-1_4 fatcat:ql5fxjhn65go5gndj2g5jjraou

Discovering Social Networks Instantly: Moving Process Mining Computations to the Database and Data Entry Time [chapter]

Alifah Syamsiyah, Boudewijn F. van Dongen, Wil M. P. van der Aalst
2017 Lecture Notes in Business Information Processing  
By moving computation both in location (to database) and time (to recording time), the discovery of social networks in a process context becomes truly scalable.  ...  To be able to deal with large data sets or with an environment which requires repetitive discoveries during the analysis, and still provide results instantly, we use an approach where most of the computation  ...  Enabling Social Network Discovery in Database As mentioned before, process mining needs the so-called input event log.  ... 
doi:10.1007/978-3-319-59466-8_4 fatcat:b543kfqikvcmfeb4wzmfi7ikmi

Process discovery using in-database minimum self distance abstractions

Alifah Syamsiyah, Sander J. J. Leemans
2020 Proceedings of the 35th Annual ACM Symposium on Applied Computing  
The DF auto-update in DB-XES is adapted in [18] to establish Incremental Inductive Miner, which utilizes IMd and adds the ability to cope with recurrent process discovery.  ...  Our approach also enables process discovery on large and complex data sets, since it only imports the DF and MSD abstractions (and not the logs) into memory.  ... 
doi:10.1145/3341105.3373846 dblp:conf/sac/SyamsiyahL20 fatcat:5ibvoda63na3tmzil7zj5vcn74

JXES: JSON Support for the XES Event Log Standard [article]

Madhavi Bangalore Shankara Narayana, Hossameldin Khalifa, Wil van der Aalst
2020 arXiv   pre-print
Process mining assumes the existence of an event log where each event refers to a case, an activity, and a point in time.  ...  In this paper, we present JXES, the JSON standard for the event logs and also provide implementation in ProM for importing and exporting event logs in JSON format using 4 different parsers.  ...  ProM [2] is a process mining framework that contains a large set of pre-processing, process discovery, conformance and performance/enhancement algorithms.  ... 
arXiv:2009.06363v1 fatcat:kutkj6f24ndq7nqnwgdsiryqwm

Increasing Scalability of Process Mining using Event Dataframes: How Data Structure Matters [article]

Alessandro Berti
2019 arXiv   pre-print
Many algorithms, and a general-purpose open source framework (ProM 6), have been developed in the last years for process discovery, conformance checking, machine learning on event data.  ...  In this paper, we propose the usage of mainstream columnar storages and dataframes to increase the scalability of process mining.  ...  deficit, and DB-XES [17] that use relational databases to support some intermediate calculations.  ... 
arXiv:1907.12817v2 fatcat:o6yog3qj4rf4hptukqqadlddwe

SSGA and MSGA: two seed-growing algorithms for constructing collaborative subnetworks

Xiaohui Ji, Su Chen, Jun Cheng Li, Wenping Deng, Zhigang Wei, Hairong Wei
2017 Scientific Reports  
" and linked with an edge in the collaborative network.  ...  Similar behavior, in this case, can be interpreted as similar trends, peaks and nadirs in the full or partial expression profiles.  ...  Acknowledgements The manuscript was read and commented by Dr. Jennifer Sanders. This work was supported by a scholarship from the China Scholarship Council to X.J.  ... 
doi:10.1038/s41598-017-01556-z pmid:28469138 pmcid:PMC5431152 fatcat:trrhjy74bnc6xctiutisd7uqqa

JXES : JSON Support for the XES Event Log Standard

Madhavi Bangalore Shankara Narayana, Hossameldin Khalifa, Wil M. P. van der Aalst
2020
Process mining assumes the existence of an event log where each event refers to a case, an activity, and a point in time.  ...  In this paper, we present JXES, the JSON standard for the event logs and also provide implementation in ProM for importing and exporting event logs in JSON format using 4 different parsers.  ...  ProM [2] is a process mining framework that contains a large set of pre-processing, process discovery, conformance and performance/enhancement algorithms.  ... 
doi:10.18154/rwth-2020-11539 fatcat:imyqxdp7vrhzhmggbhljllfvoi