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X-WR-CALNAME;VALUE=TEXT:Eventi DIAG
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TZID:Europe/Paris
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DTSTART:20251026T030000
TZOFFSETFROM:+0200
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RDATE:20261025T030000
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DTSTART:20260329T020000
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UID:calendar.30784.field_data.0@www.diag.uniroma1.it
DTSTAMP:20260430T170948Z
CREATED:20260429T221138Z
DESCRIPTION:Abstract: Process mining leverages event data to analyze and im
 prove the execution of business processes\, supporting tasks such as proce
 ss discovery\, anomaly detection\, and next-activity prediction. Tradition
 ally\, these techniques have relied on frequency-based methods\, focusing 
 on how often certain activity sequences occur in event logs. A growing bod
 y of research now explores semantics-aware process mining\, which incorpor
 ates the meaning of activities — often expressed through textual labels — 
 into analysis\, driven by advances in large language models (LLMs). In thi
 s talk\, Prof. Van der Aa will discuss the potential benefits of semantics
 -aware process mining\, present results from current experiments on few-sh
 ot learning\, fine-tuning\, and instruction tuning\, and outline ongoing r
 esearch directions and further opportunities in this area. Bio: Han van de
 r Aa is a Professor of Process-Oriented Information Systems at the Faculty
  of Computer Science of the University of Vienna. His research centers on 
 process mining—the data-driven analysis of organizational processes—with t
 he aim of understanding\, analyzing\, and improving how organizations oper
 ate. In this context\, he is particularly interested in considerations of 
 uncertainty\, data privacy\, applications of natural language processing\,
  and the provision of results that are meaningful to users.Before joining 
 the University of Vienna in 2024\, Han van der Aa obtained a PhD from the 
 Vrije Universiteit Amsterdam in 2018 and previously held positions at the 
 Humboldt-Universität zu Berlin and the University of Mannheim. His work ha
 s resulted in close to 100 peer-reviewed publications\, which have won awa
 rds at flagship conferences in the field\, such as CAISE\, BPM\, and ICPM.
  
DTSTART;TZID=Europe/Paris:20260512T143000
DTEND;TZID=Europe/Paris:20260512T143000
LAST-MODIFIED:20260430T063020Z
LOCATION:Aula Magna\, DIAG
SUMMARY:Semantics-Aware Process Mining: Benefits\, Current State\, and Oppo
 rtunities - Han van der Aa
URL;TYPE=URI:https://www.diag.uniroma1.it/node/30784
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