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Mini-Process Cubes: Enabling Real-Time Analysis and Process Discovery in Stream Process Mining

https://doi.org/10.2139/ssrn.4656941
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-02671-4_6openalex-extracted
Applying Sequence Mining for Outlier Detection in Process Mining
inferredcites →https://doi.org/10.1007/978-3-030-21571-2_14openalex-extracted
Generalized Alignment-Based Trace Clustering of Process Behavior
inferredcites →https://doi.org/10.1007/978-3-031-08848-3_11openalex-extracted
Streaming Process Mining
inferredcites →https://doi.org/10.1007/978-3-319-02922-1_1openalex-extracted
Process Cubes: Slicing, Dicing, Rolling Up and Drilling Down Event Data for Process Mining
inferredcites →https://doi.org/10.1007/978-3-319-19237-6_7openalex-extracted
Multidimensional Process Mining Using Process Cubes
inferredcites →https://doi.org/10.1007/978-3-319-42887-1_15openalex-extracted
Clustering Traces Using Sequence Alignment
inferredcites →https://doi.org/10.1007/978-3-319-69904-2_24openalex-extracted
Alignment-Based Trace Clustering
inferredcites →https://doi.org/10.1007/978-3-319-91563-0_17openalex-extracted
Detection and Interactive Repair of Event Ordering Imperfection in Process Logs
inferredcites →https://doi.org/10.1007/978-3-319-91563-0_3openalex-extracted
Filtering Spurious Events from Event Streams of Business Processes
inferredcites →https://doi.org/10.1007/978-3-319-93931-5_9openalex-extracted
Repairing Outlier Behaviour in Event Logs
inferredcites →https://doi.org/10.1007/978-3-642-00328-8_11openalex-extracted
Trace Clustering in Process Mining
inferredcites →https://doi.org/10.1007/978-3-642-12186-9_16openalex-extracted
Trace Clustering Based on Conserved Patterns: Towards Achieving Better Process Models
inferredcites →https://doi.org/10.1007/s10844-018-0507-6openalex-extracted
Discovering more precise process models from event logs by filtering out chaotic activities
inferredcites →https://doi.org/10.1016/j.is.2016.07.011openalex-extracted
Event log imperfection patterns for process mining: Towards a systematic approach to cleaning event logs
inferredcites →https://doi.org/10.1093/comjnl/bxx040openalex-extracted
Divide and Conquer: A Tool Framework for Supporting Decomposed Discovery in Process Mining
inferredcites →https://doi.org/10.1109/access.2019.2894905openalex-extracted
A Profile Clustering Based Event Logs Repairing Approach for Process Mining
inferredcites →https://doi.org/10.1109/mci.2009.935307openalex-extracted
Process Discovery: Capturing the Invisible
inferredcites →https://doi.org/10.1109/tkde.2004.47openalex-extracted
Workflow mining: discovering process models from event logs
inferredcites →https://doi.org/10.1109/tkde.2013.64openalex-extracted
Active Trace Clustering for Improved Process Discovery
inferredcites →https://doi.org/10.1109/tkde.2016.2594785openalex-extracted
Efficient Recovery of Missing Events
inferredcites →https://doi.org/10.1109/tkde.2016.2614680openalex-extracted
Filtering Out Infrequent Behavior from Business Process Event Logs
inferredcites →https://doi.org/10.1109/tsc.2020.3004532openalex-extracted
Evaluation Goals for Online Process Mining: A Concept Drift Perspective
inferredcites →https://doi.org/10.1137/1.9781611972795.35openalex-extracted
Context Aware Trace Clustering: Towards Improving Process Mining Results
inferredcites →https://doi.org/10.1145/248603.248616openalex-extracted
An overview of data warehousing and OLAP technology
inferredcites →https://doi.org/10.30534/ijatcse/2020/141942020openalex-extracted
Challenges and Use Cases of Process Discovery in Process Mining
inferredcites →https://doi.org/10.3390/app112210556openalex-extracted
Event Log Preprocessing for Process Mining: A Review
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.