New Employee: Zahra Valizadeh

Zahra1Zahra Valizadeh-Gh received her BSc. degree in applied mathematics from Kharazmi University, Tehran, Iran, in 2005, the MSc. degree in the same major from Sharif University of Technology, Tehran, Iran, in 2007, and the PhD. degree in numerical optimization from the Islamic Azad University (IAU), Iran, in 2012. Since 2012, she has been Assistant Professor at IAU. Now, she has joint to Information Systems Group as a visiting researcher for six mounths. Her research interests include the fuzzy logic, systems of fuzzy equations and systems of fuzzy relational equations/inequalities as well as the multi-criteria optimization theory.

Journal articles:

Z . Valizadeh-Gh, E . Khorram (2015) Linear Fractional Multi-Objective Optimization Problems Subject to Fuzzy Relational Equations with the Max-Average Composition, Applied and Computational Mathematics. Special Issue: New Advances in Fuzzy Mathematics: Theory, Algorithms, and Applications, 4(1-2), 20-30.

E. Khorram, R. Ezzati, Z. Valizadeh (2014) Linear fractional multi-objective optimization problems subject to fuzzy relational equations with a continuous Archimedean triangular norm, Information Sciences, 267, 225-239.

R. Ezzati, S. Khezerloo, N. Mahdavi-Amiri, Z. Valizadeh (2014) Approximate Non-negative Symmetric Solution of Fully Fuzzy Systems Using Median IntervalDefuzzi_cation, Fuzzy Information and Engineering, 6, 1-28.

E. Khorram, R. Ezzati, Z. Valizadeh (2012) Solving nonlinear multi-objective optimization problems with fuzzy relation inequality constraints regarding Archimedean triangular norm compositions, Fuzzy Optimization and Decision Making, 11(3), 299-335.

R. Ezzati, S. Khezerloo, N. Mahdavi-Amiri, Z. Valizadeh (2012) New Models and Algorithms for Approximate Solutions of Single-Signed Fully Fuzzy LR Linear Systems, Iranian Journal of Fuzzy Systems, 10(3), 1-26.

Z. Valizadeh, R. Ezzati, S. Khezerloo (2012) Approximate Symmetric Solution of Dual Fuzzy Systems Regarding Two Di_erent Fuzzy Multiplications, Indian Journal of Science and Technology, 5 (2), 2100-2112.

S. Khezerloo, M. Montazeri, Z. Valizadeh (2010) A New Method for Solving Fuzzy Linear System, International Journal of Industrial Mathematics, 2 (2), 97-104.

Presentation by Arthur ter Hofstede: Event Log Imperfection Patterns for Process Mining

Title: Event Log Imperfection Patterns for Process Mining

Presented by Arthur HM ter Hofstede

Based on joint work with Suriadi Suriadi, Rob Andrews and Moe Wynn

Abstract

An essential component of a process mining exercise is the ability
to properly prepare the log(s) for analysis. This entails detecting various
types of errors and deficiencies as the quality of the analysis heavily
depends on the quality of the event log. Unfortunately this is not a trivial task
and much depends on the skills and experiences of the analyst(s) involved.
In order to more systematically approach log preparation and to
reduce the dependency on specialist skills, a set of patterns is proposed.
These patterns aim to capture the various types of issues that may be encountered,
the way they may manifest themselves, how they may influence analysis results,
and potential remedies to counter these issues.

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