An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs
In this paper, we carry out an experimental analytics to show how much perfectly the conceptual mining framework is operable on re-discovering workflow process patterns and their enacted proportions from the workflow enactment event histories logged in a format of XES standardized schema. In princip...
Gespeichert in:
Veröffentlicht in: | Wireless networks 2022-04, Vol.28 (3), p.1211-1218 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1218 |
---|---|
container_issue | 3 |
container_start_page | 1211 |
container_title | Wireless networks |
container_volume | 28 |
creator | Kim, Kyoungsook Lee, Young-Koo Ahn, Hyun Kim, Kwanghoon Pio |
description | In this paper, we carry out an experimental analytics to show how much perfectly the conceptual mining framework is operable on re-discovering workflow process patterns and their enacted proportions from the workflow enactment event histories logged in a format of XES standardized schema. In principle, the framework must be able to properly handle all the workflow process patterns based upon the four types of control-flow primitives such as linear (sequential), disjunctive (selective), conjunctive (parallel), and loop (iterative) process patterns. The paper focuses on implementing an algorithmic mining framework only for discovering all the process patterns and their enacted proportions. To prove the functional correctness of the framework, we carry out an experimental mining and analytics on the real workflow instance enactment event histories of 10,000 workcases, and we finally visualize the mining and analytic artifacts and describe the implications of the results of the experiment. |
doi_str_mv | 10.1007/s11276-018-01899-z |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2637648550</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2637648550</sourcerecordid><originalsourceid>FETCH-LOGICAL-c347t-ed4a6d9a940662c9f0f1c9f88c75ff561b5330e23f279eb54b7d652277a687893</originalsourceid><addsrcrecordid>eNp9kUtLAzEUhYMoWKt_wFXA9Wgek9eyFF9QcKPrkGaSMnU6GZNpa_vrzTiCuy7uTUK-c7jcA8AtRvcYIfGQMCaCFwjLoZQqjmdggpkghcSKn-c7IqRAiMpLcJXSGiEkqVITsJ210H13LtYb1_amgZu6rdsVNG2VyzSHvrYJ-hBhVScbdhnMv10MXYh9HTIxPKxLCXam711sMx3DBu5D_PRN2EPXGtsP5tDtht6EVboGF940yd38nVPw8fT4Pn8pFm_Pr_PZorC0FH3hqtLwShlVIs6JVR55nLuUVjDvGcdLRilyhHoilFuycikqzggRwnAppKJTcDf65hm_ti71eh22MQ-dNOFU8FIyhk5SmClEqJQ8U2SkbAwpRed1l5dm4kFjpIcQ9BiCzgHo3xD0MYvoKErdsDgX_61PqH4AEaCMmg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2159023886</pqid></control><display><type>article</type><title>An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs</title><source>SpringerNature Complete Journals</source><creator>Kim, Kyoungsook ; Lee, Young-Koo ; Ahn, Hyun ; Kim, Kwanghoon Pio</creator><creatorcontrib>Kim, Kyoungsook ; Lee, Young-Koo ; Ahn, Hyun ; Kim, Kwanghoon Pio</creatorcontrib><description>In this paper, we carry out an experimental analytics to show how much perfectly the conceptual mining framework is operable on re-discovering workflow process patterns and their enacted proportions from the workflow enactment event histories logged in a format of XES standardized schema. In principle, the framework must be able to properly handle all the workflow process patterns based upon the four types of control-flow primitives such as linear (sequential), disjunctive (selective), conjunctive (parallel), and loop (iterative) process patterns. The paper focuses on implementing an algorithmic mining framework only for discovering all the process patterns and their enacted proportions. To prove the functional correctness of the framework, we carry out an experimental mining and analytics on the real workflow instance enactment event histories of 10,000 workcases, and we finally visualize the mining and analytic artifacts and describe the implications of the results of the experiment.</description><identifier>ISSN: 1022-0038</identifier><identifier>EISSN: 1572-8196</identifier><identifier>DOI: 10.1007/s11276-018-01899-z</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Communications Engineering ; Computer Communication Networks ; Computer engineering ; Electrical Engineering ; Engineering ; Experiments ; Information control ; IT in Business ; Mathematical analysis ; Networks ; Wireless networks ; Workflow</subject><ispartof>Wireless networks, 2022-04, Vol.28 (3), p.1211-1218</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2018</rights><rights>Wireless Networks is a copyright of Springer, (2018). All Rights Reserved.</rights><rights>Springer Science+Business Media, LLC, part of Springer Nature 2018.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c347t-ed4a6d9a940662c9f0f1c9f88c75ff561b5330e23f279eb54b7d652277a687893</citedby><cites>FETCH-LOGICAL-c347t-ed4a6d9a940662c9f0f1c9f88c75ff561b5330e23f279eb54b7d652277a687893</cites><orcidid>0000-0001-6320-2556</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11276-018-01899-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11276-018-01899-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Kim, Kyoungsook</creatorcontrib><creatorcontrib>Lee, Young-Koo</creatorcontrib><creatorcontrib>Ahn, Hyun</creatorcontrib><creatorcontrib>Kim, Kwanghoon Pio</creatorcontrib><title>An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs</title><title>Wireless networks</title><addtitle>Wireless Netw</addtitle><description>In this paper, we carry out an experimental analytics to show how much perfectly the conceptual mining framework is operable on re-discovering workflow process patterns and their enacted proportions from the workflow enactment event histories logged in a format of XES standardized schema. In principle, the framework must be able to properly handle all the workflow process patterns based upon the four types of control-flow primitives such as linear (sequential), disjunctive (selective), conjunctive (parallel), and loop (iterative) process patterns. The paper focuses on implementing an algorithmic mining framework only for discovering all the process patterns and their enacted proportions. To prove the functional correctness of the framework, we carry out an experimental mining and analytics on the real workflow instance enactment event histories of 10,000 workcases, and we finally visualize the mining and analytic artifacts and describe the implications of the results of the experiment.</description><subject>Algorithms</subject><subject>Communications Engineering</subject><subject>Computer Communication Networks</subject><subject>Computer engineering</subject><subject>Electrical Engineering</subject><subject>Engineering</subject><subject>Experiments</subject><subject>Information control</subject><subject>IT in Business</subject><subject>Mathematical analysis</subject><subject>Networks</subject><subject>Wireless networks</subject><subject>Workflow</subject><issn>1022-0038</issn><issn>1572-8196</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kUtLAzEUhYMoWKt_wFXA9Wgek9eyFF9QcKPrkGaSMnU6GZNpa_vrzTiCuy7uTUK-c7jcA8AtRvcYIfGQMCaCFwjLoZQqjmdggpkghcSKn-c7IqRAiMpLcJXSGiEkqVITsJ210H13LtYb1_amgZu6rdsVNG2VyzSHvrYJ-hBhVScbdhnMv10MXYh9HTIxPKxLCXam711sMx3DBu5D_PRN2EPXGtsP5tDtht6EVboGF940yd38nVPw8fT4Pn8pFm_Pr_PZorC0FH3hqtLwShlVIs6JVR55nLuUVjDvGcdLRilyhHoilFuycikqzggRwnAppKJTcDf65hm_ti71eh22MQ-dNOFU8FIyhk5SmClEqJQ8U2SkbAwpRed1l5dm4kFjpIcQ9BiCzgHo3xD0MYvoKErdsDgX_61PqH4AEaCMmg</recordid><startdate>20220401</startdate><enddate>20220401</enddate><creator>Kim, Kyoungsook</creator><creator>Lee, Young-Koo</creator><creator>Ahn, Hyun</creator><creator>Kim, Kwanghoon Pio</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7SP</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M2P</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0001-6320-2556</orcidid></search><sort><creationdate>20220401</creationdate><title>An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs</title><author>Kim, Kyoungsook ; Lee, Young-Koo ; Ahn, Hyun ; Kim, Kwanghoon Pio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c347t-ed4a6d9a940662c9f0f1c9f88c75ff561b5330e23f279eb54b7d652277a687893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Communications Engineering</topic><topic>Computer Communication Networks</topic><topic>Computer engineering</topic><topic>Electrical Engineering</topic><topic>Engineering</topic><topic>Experiments</topic><topic>Information control</topic><topic>IT in Business</topic><topic>Mathematical analysis</topic><topic>Networks</topic><topic>Wireless networks</topic><topic>Workflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Kyoungsook</creatorcontrib><creatorcontrib>Lee, Young-Koo</creatorcontrib><creatorcontrib>Ahn, Hyun</creatorcontrib><creatorcontrib>Kim, Kwanghoon Pio</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>ProQuest Central China</collection><jtitle>Wireless networks</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Kyoungsook</au><au>Lee, Young-Koo</au><au>Ahn, Hyun</au><au>Kim, Kwanghoon Pio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs</atitle><jtitle>Wireless networks</jtitle><stitle>Wireless Netw</stitle><date>2022-04-01</date><risdate>2022</risdate><volume>28</volume><issue>3</issue><spage>1211</spage><epage>1218</epage><pages>1211-1218</pages><issn>1022-0038</issn><eissn>1572-8196</eissn><abstract>In this paper, we carry out an experimental analytics to show how much perfectly the conceptual mining framework is operable on re-discovering workflow process patterns and their enacted proportions from the workflow enactment event histories logged in a format of XES standardized schema. In principle, the framework must be able to properly handle all the workflow process patterns based upon the four types of control-flow primitives such as linear (sequential), disjunctive (selective), conjunctive (parallel), and loop (iterative) process patterns. The paper focuses on implementing an algorithmic mining framework only for discovering all the process patterns and their enacted proportions. To prove the functional correctness of the framework, we carry out an experimental mining and analytics on the real workflow instance enactment event histories of 10,000 workcases, and we finally visualize the mining and analytic artifacts and describe the implications of the results of the experiment.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11276-018-01899-z</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-6320-2556</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1022-0038 |
ispartof | Wireless networks, 2022-04, Vol.28 (3), p.1211-1218 |
issn | 1022-0038 1572-8196 |
language | eng |
recordid | cdi_proquest_journals_2637648550 |
source | SpringerNature Complete Journals |
subjects | Algorithms Communications Engineering Computer Communication Networks Computer engineering Electrical Engineering Engineering Experiments Information control IT in Business Mathematical analysis Networks Wireless networks Workflow |
title | An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T09%3A49%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20experimental%20mining%20and%20analytics%20for%20discovering%20proportional%20process%20patterns%20from%20workflow%20enactment%20event%20logs&rft.jtitle=Wireless%20networks&rft.au=Kim,%20Kyoungsook&rft.date=2022-04-01&rft.volume=28&rft.issue=3&rft.spage=1211&rft.epage=1218&rft.pages=1211-1218&rft.issn=1022-0038&rft.eissn=1572-8196&rft_id=info:doi/10.1007/s11276-018-01899-z&rft_dat=%3Cproquest_cross%3E2637648550%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2159023886&rft_id=info:pmid/&rfr_iscdi=true |