Business Process Intelligence

Grigori, Daniela; Casati, Fabio; Castellanos, Malú; Dayal, Umeshwar; Sayal, Mehmet; Shan, Ming-Chien

doi:10.1016/j.compind.2003.10.007

Cited by 392 publications

(246 citation statements)

References 17 publications

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“…In more general work on BPA, we find techniques based on plain statistical analysis, data and process mining techniques, neural networks, case-based reasoning, or heuristic rules [13,7,14,15,16,17,18]. Some techniques focus on automating analysis to the greatest extent whereas others pay particular attention to obtaining results that can easily be explained and presented to the user.…”

Section: Related Workmentioning

confidence: 99%

Strategy-Driven Business Process Analysis

Pedrinaci

Marković

Hasibether

et al. 2009

Business Information Systems

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Abstract. Business Process Analysis (BPA) aims to verify, validate, and identify potential improvements for business processes. Despite the wide range of technologies developed so far, the large amount of information that needs to be integrated and processed, as well as the quantity of data that has to be produced and presented still poses important challenges both from a processing and presentation perspectives. We argue that to enhance BPA, semantics have to be the core backbone in order to better support the application of analysis techniques on the first hand, and to guide the computation and presentation of the results on the other hand. We propose a knowledge-based approach to supporting strategydriven BPA by making use of a comprehensive and extensible ontological framework capturing from high-level strategic concerns down to lowerlevel monitoring information. We describe how corporate strategies can be operationalized into concrete analysis that can guide the evaluation of organisational processes, structure the presentation of results obtained and better help assess the well-being of corporate business processes.

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Section: Related Workmentioning

confidence: 99%

Strategy-Driven Business Process Analysis

Pedrinaci

Marković

Hasibether

et al. 2009

Business Information Systems

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“…Please note that an exclusive choice with overlapping rules is different to an inclusive choice, which allows multiple alternatives activities to be executed in parallel. State of the art techniques [3,5,6] only use decision trees, and, hence, cannot discover this class of rules. For instance, current techniques fail to discover the decision rule in Fig.…”

Section: Introductionmentioning

confidence: 99%

“…The technique is able to deliberately trade the precision of mutually-exclusive rules, i.e., only one alternative is possible, against fitness, i.e., the overlapping rules that are less often violated. In short, as in [3,5,6], our technique builds an initial decision tree based on observations from the event log. Then, for each decision tree leaf, the wrongly classified instances are used to learn a new decision tree leading to new rules.…”

Section: Introductionmentioning

confidence: 99%

“…Rules defined over the process data are an integral part of this process. Traditionally, decision mining methods [3,5,6] use decision tree learning techniques such as C4.5 [7] to determine rules governing the process execution based on event logs. For example, attribute values recorded for status and amount are used as feature, while the choice between Payment, Send Fine, Close Fine is used as target class.…”

Section: Introductionmentioning

confidence: 99%

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Decision Mining Revisited - Discovering Overlapping Rules

Mannhardt

Leoni

Reijers

et al. 2016

Advanced Information Systems Engineering

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“…In order to attract and retain customers as well as business partners, organizations need to provide their services (i.e., execute their processes) with a high consistent, and predictable quality [4]. Many companies work very hard to produce goods and services to a high standard.…”

Section: Related Studiesmentioning

confidence: 99%

Development of an OLAP-Fuzzy Based Process Mining System for Quality Improvement

Ho¹,

Lau²

IFIP International Federation for Information Processing

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Abstract:Currently, companies active in the development of high-tech products has become more and more complex in the age of mass customization. Not only do they have to focus on improving product quality, but rather on gaining experience to modify the current processes in order to streamline the integrated workflow. A real-time process mining system (R-PMS) is developed to analyze the proposed XML based process data for discovering the hid-den relationship between processes. The new feature of this system is the in-corporation of the process mining engine, which is characterized by the combined capabilities of the Online Analytical Processing (OLAP) and fuzzy logic (FL), to form a robust framework for highlighting the undesirable process set-ting and parameters for further improvement in a real-time manner. The simulation results indicate that the OLAP based fuzzy approach is generally superior to those of conventional methods which offer higher flexibility on production process management with decision support ability, in this paper, the de-tailed architecture and a case study are included to demonstrate the feasibility of the proposed system.

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Business Process Intelligence

Cited by 392 publications

References 17 publications

Strategy-Driven Business Process Analysis

Strategy-Driven Business Process Analysis

Decision Mining Revisited - Discovering Overlapping Rules

Development of an OLAP-Fuzzy Based Process Mining System for Quality Improvement

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