Data Mining Tool Selection

2011 ◽  
pp. 511-518
Author(s):  
Christophe Giraud-Carrier
Keyword(s):  
Data Mining ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Tool Selection ◽  
Business Decision ◽  
Software Packages ◽  
Or Methodology ◽  
Business Requirement

It is sometimes argued that all one needs to engage in Data Mining (DM) is data and a willingness to “give it a try.” Although this view is attractive from the perspective of enthusiastic DM consultants who wish to expand the use of the technology, it can only serve the purposes of one-shot proofs of concept or preliminary studies. It is not representative of the complex reality of deploying DM within existing business processes. In such contexts, one needs two additional ingredients: a process model or methodology, and supporting tools. Several Data Mining process models have been developed (Fayyad et al, 1996; Brachman & Anand, 1996; Mannila, 1997; Chapman et al, 2000), and although each sheds a slightly different light on the process, their basic tenets and overall structure are essentially the same (Gaul & Saeuberlich, 1999). A recent survey suggests that virtually all practitioners follow some kind of process model when applying DM and that the most widely used methodology is CRISP-DM (KDnuggets Poll, 2002). Here, we focus on the second ingredient, namely, supporting tools. The past few years have seen a proliferation of DM software packages. Whilst this makes DM technology more readily available to non-expert end-users, it also creates a critical decision point in the overall business decision-making process. When considering the application of Data Mining, business users now face the challenge of selecting, from the available plethora of DM software packages, a tool adequate to their needs and expectations. In order to be informed, such a selection requires a standard basis from which to compare and contrast alternatives along relevant, business-focused dimensions, as well as the location of candidate tools within the space outlined by these dimensions. To meet this business requirement, a standard schema for the characterization of Data Mining software tools needs to be designed.

Development of BPMN Architecture using Integration of Data Mining

2018 ◽  
Vol 6 (8) ◽  
pp. 256
Author(s):  
Ritu Saluja ◽  
S. K. Singh ◽  
A. K. Chaturvedi
Keyword(s):  
Data Mining ◽  
Business Process ◽  
Process Model ◽  
Process Management ◽  
Business Processes ◽  
Machine Learning Techniques ◽  
Business Decision ◽  
Management Framework ◽  
Learning Techniques ◽  
Modern Business

Data mining is an important factor of success for modern business processes. Modern Integrating data mining with business solutions will improve the business process model (BPM) and enhance the overall business process management framework. The proposed architecture promises to provide great support for flexible design, deployment and managementof business processes. Incorporating services of data mining in order to choose the appropriate business model, determining missing standards and deploying machine learning techniques in an applicable manner is a challenging task discussed in the paper. Theproposed work describes the overall contribution of data mining services and validates the novelty in architecture by defining user roles for business, decision mining and IT standards. Supervised and unsupervised learning technique is used for determining similarity between the proposed model and the previously stored models.

scholarly journals Business processes exceptions in relation to operational performance

2019 ◽  
Vol 25 (5) ◽  
pp. 908-922 ◽  
Author(s):  
Remco Dijkman ◽  
Oktay Turetken ◽  
Geoffrey Robert van IJzendoorn ◽  
Meint de Vries
Keyword(s):  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Operational Performance ◽  
Normal Flow ◽  
Throughput Time ◽  
Content Type ◽  
Business Process Models ◽  
Practical Implications

Purpose Business process models describe the way of working in an organization. Typically, business process models distinguish between the normal flow of work and exceptions to that normal flow. However, they often present an idealized view. This means that unexpected exceptions – exceptions that are not modeled in the business process model – can also occur in practice. This has an effect on the efficiency of the organization, because information systems are not developed to handle unexpected exceptions. The purpose of this paper is to study the relation between the occurrence of exceptions and operational performance. Design/methodology/approach The paper does this by analyzing the execution logs of business processes from five organizations, classifying execution paths as normal or exceptional. Subsequently, it analyzes the differences between normal and exceptional paths. Findings The results show that exceptions are related to worse operational performance in terms of a longer throughput time and that unexpected exceptions relate to a stronger increase in throughput time than expected exceptions. Practical implications These findings lead to practical implications on policies that can be followed with respect to exceptions. Most importantly, unexpected exceptions should be avoided by incorporating them into the process – and thus transforming them into expected exceptions – as much as possible. Also, as not all exceptions lead to longer throughput times, continuous improvement should be employed to continuously monitor the occurrence of exceptions and make decisions on their desirability in the process. Originality/value While work exists on analyzing the occurrence of exceptions in business processes, especially in the context of process conformance analysis, to the best of the authors’ knowledge this is the first work that analyzes the possible consequences of such exceptions.

scholarly journals Pengujian Unit Plugin Pemberian Anotasi Efek Secara Semantik pada Proses Bisnis BPMN

2021 ◽  
Vol 6 (3) ◽  
pp. 170
Author(s):  
Hilman Nuril Hadi
Keyword(s):  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Unit Testing ◽  
Business Process Model ◽  
Testing Technique ◽  
Modeling Tools ◽  
Path Testing ◽  
Future Business

Business process model was created to make it easier for business process stakeholders to communicate and discuss the structure of the process more effectively and efficiently. Business process models can also be business artifacts and media that can be analyzed further to improve and maintain organizational competitiveness. To analyze business processes in a structured manner, the effect/results of the execution of business processes will be one of the important information. The effect/result of the execution of certain activities or a business process as a whole are useful for managing business processes, including for improvements related to future business processes. This effect annotation approach needs to be supported by business process modeling tools to assist business analysts in managing business processes properly. In previous research, the author has developed a plugin that supports business analysts to describe the effects semantically attached to activities in the Business Process Model and Notation (BPMN) business process model. In this paper, the author describes the unit testing process and its results on the plugin of semantic effect annotation that have been developed. Unit testing was carried out using the basic path testing technique and has obtained three test paths. The results of unit test for plugin are also described in this paper.

scholarly journals Improving the performance of process discovery algorithms by instance selection

2020 ◽  
Vol 17 (3) ◽  
pp. 927-958
Author(s):  
Mohammadreza Sani ◽  
Sebastiaan van Zelst ◽  
Aalst van der
Keyword(s):  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Instance Selection ◽  
Event Data ◽  
Process Discovery ◽  
Selection Strategies ◽  
Speed Up ◽  
The Right ◽  
Discovery Algorithms

Process discovery algorithms automatically discover process models based on event data that is captured during the execution of business processes. These algorithms tend to use all of the event data to discover a process model. When dealing with large event logs, it is no longer feasible using standard hardware in limited time. A straightforward approach to overcome this problem is to down-size the event data by means of sampling. However, little research has been conducted on selecting the right sample, given the available time and characteristics of event data. This paper evaluates various subset selection methods and evaluates their performance on real event data. The proposed methods have been implemented in both the ProM and the RapidProM platforms. Our experiments show that it is possible to considerably speed up discovery using instance selection strategies. Furthermore, results show that applying biased selection of the process instances compared to random sampling will result in simpler process models with higher quality.

scholarly journals Collaborative method to maintain business process models updated

2014 ◽  
Vol 11 (2) ◽  
pp. 461-480 ◽  
Author(s):  
Nuno Castela ◽  
Paulo Dias ◽  
Marielba Zacarias ◽  
José Tribolet
Keyword(s):  
Case Studies ◽  
Business Process ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Organizational Environment ◽  
Business Process Model ◽  
Business Process Models ◽  
Definition Of ◽  
Over Time

Business process models are often forgotten after their creation and its representation is not usually updated. This appears to be negative as processes evolve over time. This paper discusses the issue of business process models maintenance through the definition of a collaborative method that creates interaction contexts enabling business actors to discuss about business processes, sharing business knowledge. The collaboration method extends the discussion about existing process representations to all stakeholders promoting their update. This collaborative method contributes to improve business process models, allowing updates based in change proposals and discussions, using a groupware tool that was developed. Four case studies were developed in real organizational environment. We came to the conclusion that the defined method and the developed tool can help organizations to maintain a business process model updated based on the inputs and consequent discussions taken by the organizational actors who participate in the processes.

Ontology-Based Framework for Quality in Configurable Process Models

2020 ◽  
pp. 464-478
Author(s):  
Loubna El Faquih ◽  
Mounia Fredj
Keyword(s):  
Business Process ◽  
Process Modeling ◽  
Process Model ◽  
Business Processes ◽  
Research Work ◽  
Process Models ◽  
Novel Method ◽  
Ontology Languages ◽  
Variability Management

In recent years, business process modeling has increasingly drawn the attention of enterprises. As a result of the wide use of business processes, redundancy problems have arisen and researchers introduced the variability management, in order to enhance the business process reuse. The most approach used in this context is the Configurable Process Model solution, which consists in representing the variable and the fixed parts together in a unique model. Due to the increasing number of variants, the configurable models become complex and incomprehensible, and their quality is therefore impacted. Most of research work is limited to the syntactic quality of process variants. The approach presented in this paper aims at providing a novel method towards syntactic verification and semantic validation of configurable process models based on ontology languages. We define validation rules for assessing the quality of configurable process models. An example in the e-healthcare domain illustrates the main steps of our approach.

scholarly journals A Pattern Based Method for Simplifying a BPMN Process Model

2019 ◽  
Vol 9 (11) ◽  
pp. 2322 ◽  
Author(s):  
Mateo Ramos-Merino ◽  
Luis M. Álvarez-Sabucedo ◽  
Juan M. Santos-Gago ◽  
Francisco de Arriba-Pérez
Keyword(s):  
Real World ◽  
Process Model ◽  
Business Processes ◽  
Process Models ◽  
Automatic Method ◽  
Business Process Model ◽  
Two Phase ◽  
Intensive Use ◽  
Fully Automatic ◽  
Validation Testing

BPMN (Business Process Model and Notation) is currently the preferred standard for the representation and analysis of business processes. The elaboration of these BPMN diagrams is usually carried out in an entirely manual manner. As a result of this human-driven process, it is not uncommon to find diagrams that are not in their most simplified version possible (regarding the number of elements). This work presents a fully automatic method to simplify a BPMN process model document. A two-phase iterative algorithm to achieve this simplification is described in detail. This algorithm follows a heuristic approach that makes intensive use of a Pattern Repository. This software element is concerned with the description of feasible reductions and its enactment. The critical concept lies in the discovery of small reducible patterns in the whole model and their substitution with optimised versions. This approach has been verified through a double validation testing in total 8102 cases taken from real world BPMN process models. Details for its implementation and usage by practitioners are provided in this paper along with a comparison with other existing techniques concerned with similar goals.

scholarly journals Improvement of Business-Activities in Telecommunication Enterprises by the eTOM Business-Process Structural Model Implementation

2010 ◽  
Vol 42 (1) ◽  
pp. 45-50
Author(s):  
Olga Korzachenko ◽  
Vadim Getman
Keyword(s):  
Business Process ◽  
Process Model ◽  
Process Management ◽  
Business Processes ◽  
Structural Model ◽  
Foreign Market ◽  
Process Models ◽  
High Quality ◽  
Telecommunication Companies ◽  
High Level

Improvement of Business-Activities in Telecommunication Enterprises by the eTOM Business-Process Structural Model Implementation For now, in front of telecommunication branch enterprises of Ukraine, there is a problem of activity improvement with the purpose of granting high-quality services and maintenance of competitive position, both on internal, and on a foreign market. To solve this problem, telecommunication companies appropriate to use the mechanisms of business-oriented process management and improvement of end-to-end business-processes. The purpose of this article is a choice of effective business-process model that will allow telecommunications companies to provide modern, high quality and cost competitive services. During research, conditions of the telecommunication branch enterprises of Ukraine were investigated and key problems of their activity were revealed. Existing business-process models have been considered and analyzed and the optimal model was chosen, according to the put criteria. By results of the analysis a conclusion was drawn, that to the enterprises for business-process modeling is expedient for using eTOM - high-level system business-oriented model aimed for providing of any technological services, including IT. As advantages from introduction eTOM at the Ukrainian enterprises were analyzed.

scholarly journals Business Process Management: A Comprehensive Survey

2013 ◽  
Vol 2013 ◽  
pp. 1-37 ◽  
Author(s):  
Wil M. P. van der Aalst
Keyword(s):  
Business Process ◽  
Process Model ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
State Of The Art ◽  
Cost Savings ◽  
Process Models ◽  
Fundamental Process ◽  
Comprehensive Survey

Business Process Management (BPM) research resulted in a plethora of methods, techniques, and tools to support the design, enactment, management, and analysis of operational business processes. This survey aims to structure these results and provide an overview of the state-of-the-art in BPM. In BPM the concept of a process model is fundamental. Process models may be used to configure information systems, but may also be used to analyze, understand, and improve the processes they describe. Hence, the introduction of BPM technology has both managerial and technical ramifications and may enable significant productivity improvements, cost savings, and flow-time reductions. The practical relevance of BPM and rapid developments over the last decade justify a comprehensive survey.

Toward an integrated knowledge discovery and data mining process model

2010 ◽  
Vol 25 (1) ◽  
pp. 49-67 ◽  
Author(s):  
Sumana Sharma ◽  
Kweku-Muata Osei-Bryson
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Process Model ◽  
Process Models ◽  
Data Preparation ◽  
Important Goal ◽  
Efficiency And Effectiveness ◽  
Integrated Knowledge

AbstractThe knowledge discovery and data mining (KDDM) process models describe the various phases (e.g. business understanding, data understanding, data preparation, modeling, evaluation and deployment) of the KDDM process. They act as a roadmap for implementation of the KDDM process by presenting a list of tasks for executing the various phases. The checklist approach of describing the tasks is not adequately supported by appropriate tools, which specify ‘how’ the particular task can be implemented. This may result in tasks not being implemented. Another disadvantage is that the long checklist does not capture or leverage the dependencies that exist among the various tasks of the same and different phases. This not only makes the process cumbersome to implement, but also hinders possibilities for semi-automation of certain tasks. Given that each task in the process model serves an important goal and even affects the execution of related tasks due to the dependencies, these limitations are likely to negatively affect the efficiency and effectiveness of KDDM projects. This paper proposes an improved KDDM process model that overcomes these shortcomings by prescribing tools for supporting each task as well as identifying and leveraging dependencies among tasks for semi-automation of tasks, wherever possible.

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