[AISWorld] CfP EdbA'24 - Fifth International Workshop on Event Data and Behavioral Analytics - First deadline 8 August 2024

[Francesco Leotta]

Dear colleagues,

we would like to draw your attention to a Call for Papers for the Fifth
edition of the EdbA – Event Data & Behavioral Analytics (EdbA), colocated
with the 6th International Conference on Process Mining, October 14-18,
2024.

Details can be found here: https://edba.science/

Deadline Abstract Submission: August 8, 2024 (Anywhere on Earth)
Deadline Paper Submission: August 15, 2024 (Anywhere on Earth)
Paper Acceptance Notification: September 2, 2024 (Anywhere on Earth)
Pre-Workshop Camera Ready Version: September 23, 2024 (Anywhere on Earth)
EdbA Workshop: October 14, 2024
Post-Workshop Camera Ready Version: October 29, 2024 (Anywhere on Earth)

Workshop organizers

     Benoît Depaire (Hasselt University, The Netherlands)
     Dirk Fahland (TU/Eindhoven, The Netherlands)
     Francesco Leotta (Sapienza Università di Roma, Italy)
     Arik Senderovich (York University, Canada)

Over the past decades, capturing, storing and analyzing event data has
gained attention in various domains such as process mining, clickstream
analytics, IoT analytics, e-commerce and retail analytics, online gaming
analytics, security analytics, website traffic analytics and preventive
maintenance, smart homes and offices, just to name a few. It even resulted
in the birth of new research domains such as behavioral informatics,
behavioral analytics and behavioral operations research. The interest in
event data lies in its analytical potential as it captures the dynamic
behavior of people, objects and/or systems at a fine-grained level.

While each of these domains have their own applications and idiosyncrasies,
they share the common denominator of event data and the objective to
analyze behavior. Yet, these domains also differ in underlying assumptions
and techniques used. Therefore, the objective of this workshop is to
provide a forum to practitioners and researchers for studying a
quintessential, minimal notion of events as the common denominator for
records of discrete behavior in all its forms, and to study, develop and
discuss techniques and methods for behavioral analytics based on all kinds
of events.

The Event Data & Behavioral Analytics (EdbA) workshop considers as its
starting point the presence of event data being recorded at various sources
and contexts, being stored in various forms, and being considered for
analysis of behavior of various kinds. Event data at different levels of
granularity are considered, ranging from frequent sensor-based events in
IoT settings to recordings of aggregate or long-running behavior involving
time intervals and rich information. Behavior often involves multiple
entities, objects, and actors to which events can be correlated in various
ways. In these situations, a unique explicit process notion does either not
exist, is unclear or different processes or dynamics could be recorded in
the same dataset.

The workshop aims to further the development of new (or the novel
application of existing) techniques, algorithms and data structures for
recording, storing, managing, processing, analyzing, and visualizing event
data in various forms. The workshop welcomes two types of submissions, i.e.
original research papers as well as case study reports on event data and
behavioral analytics.

The topics considered in the workshop consist of, but are not limited to:

- Augmentation of fine-grained event data to higher-order activities or
behavior
- Storage, integration, and querying of behavioral event data
- Representation and analysis of event data without a unique case
identifier (without case identifier or with multiple case identifiers
present)
- Monitoring and detection of complex behavior
- Diagnosis of behavior, including root-cause analysis, variance analysis,
cluster analysis and many other exploratory analysis techniques
- Visual analytics of (complex) behavior
- Behavior Pattern detection, e.g., in real-time location data or other
types of context-rich data
- Outlier Behavior Detection
- Behavior Prediction
- Prescriptive analytics which predicts behavior and prescribes which
action could steer behavior in a specific direction

Best regards,

-------------------------

*Francesco Leotta*
*PhD, Associate Professor*-------------------------
SAPIENZA - Università di Roma
Dipartimento di Ingegneria Informatica, Automatica e Gestionale "A.Ruberti"
Via Ariosto 25 - 00185 Rome, Italy
-------------------------------
*Room:* B218
*Tel:* +39 06 77274012 -- +39 06 77274013
*Web:* http://www.diag.uniroma1.it/~leotta
*E-Mail: *leotta *at* diag *dot *uniroma1 *dot* it