What is he best known for?
The fields of study he is best known for:
- Programming language
- Database
- Artificial intelligence
His scientific interests lie mostly in Data mining, Process modeling, Process mining, Business process discovery and Event.
His Data mining research is multidisciplinary, incorporating elements of Process, Petri net and Process.
His biological study spans a wide range of topics, including Business Process Model and Notation, Business process and Business process modeling.
His research in Business process modeling focuses on subjects like Business process management, which are connected to Business intelligence and Data science.
Dirk Fahland integrates Business process discovery with Block in his research.
His study explores the link between Event and topics such as Conformance checking that cross with problems in Resource and Control flow.
His most cited work include:
- Process Mining Manifesto (684 citations)
- Discovering block-structured process models from event logs - a constructive approach (288 citations)
- Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour (201 citations)
What are the main themes of his work throughout his whole career to date?
Dirk Fahland focuses on Process modeling, Process, Process mining, Data mining and Software engineering.
Dirk Fahland has researched Process modeling in several fields, including Theoretical computer science, Business Process Model and Notation, Business process modeling, Artificial intelligence and Work in process.
Dirk Fahland has included themes like Quality, Machine learning and Data science in his Process study.
His Process mining study combines topics in areas such as Event, Business process discovery and Petri net.
Dirk Fahland interconnects Process and Concurrency in the investigation of issues within Data mining.
He combines subjects such as Data exchange, Artifact and Systems engineering with his study of Software engineering.
He most often published in these fields:
- Process modeling (37.98%)
- Process (36.43%)
- Process mining (32.56%)
What were the highlights of his more recent work (between 2017-2021)?
- Process mining (32.56%)
- Event (22.48%)
- Process (36.43%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Process mining, Event, Process, Data mining and Petri net.
Process mining is a subfield of Business process that Dirk Fahland explores.
His Event research incorporates elements of Variety, Queue, Process and Distributed computing.
His research in Process intersects with topics in Bottleneck and Process management.
His study on Data mining also encompasses disciplines like
- Work in process and related Business process discovery,
- Quality which connect with Model complexity.
His Process modeling study integrates concerns from other disciplines, such as Machine learning and Artificial intelligence.
Between 2017 and 2021, his most popular works were:
- Scalable process discovery and conformance checking (89 citations)
- The imprecisions of precision measures in process mining (29 citations)
- Describing Behavior of Processes with Many-to-Many Interactions (16 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Database
- Artificial intelligence
Dirk Fahland mostly deals with Process mining, Data mining, Event, Process and Conformance checking.
The subject of his Process mining research is within the realm of Business process management.
Within one scientific family, Dirk Fahland focuses on topics pertaining to Work in process under Data mining, and may sometimes address concerns connected to Big data and Scalability.
Dirk Fahland focuses mostly in the field of Event, narrowing it down to topics relating to Process and, in certain cases, Batch processing and Consistency.
His research in Process is mostly focused on Business process.
His studies in Conformance checking integrate themes in fields like Security policy and Business process discovery.
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