Process Mining Versus Intention Mining

  title={Process Mining Versus Intention Mining},
  author={Ghazaleh Khodabandelou and Charlotte Hug and R{\'e}becca Deneck{\`e}re and Camille Salinesi},
Process mining aims to discover, enhance or check the conformance of activity-oriented process models from event logs. A new field of research, called intention mining, recently emerged. This field has the same objectives as process mining but specifically addresses intentional process models (processes focused on the reasoning behind the activities). This paper aims to highlight the differences between these two fields of research and illustrates the use of mining techniques on a dataset of… 

Literature Review about Intention Mining in Information Systems

A literature review about the development of intention mining in the information systems engineering area is conducted to define the state of the art of the intention mining techniques that are have developed based on the process mining techniques.

From event logs to goals: a systematic literature review of goal-oriented process mining

A systemic literature review based on 24 papers rigorously selected from four popular search engines in 2018 is provided to assess the state of goal-oriented process mining, highlighting that the use of process mining in association with goals does not yet have a coherent line of research, whereas intention mining shows a meaningful trace of research.

A Comprehensive Review on Intents, Intention Mining and Intention Classification

This paper mainly focuses and discusses on the literature review algorithms, models and tools used in Intention Mining, hoping that this information will be useful for developing models to retrieve intentions from the traces of activities and developing various intention mining techniques.

Intention-Oriented Process Model Discovery from Incident Management Event Logs

An application of intention-oriented process mining for the domain of incident management of an Information Technology Infrastructure Library (ITIL) process, using the Map Miner Method (MMM) on a large real-world dataset for discovering hidden and unobservable user behavior, strategies and intentions.

A novel approach to process mining: Intentional process models discovery

A novel approach of process mining, called Map Miner Method (MMM), designed to automate the construction of intentional process models from process logs, which includes two specific algorithms developed to infer users' intentions and construct intentional process model (Map) respectively.

Process Mining: intentional process model generation for recommendation

This work aims to improve the conformance between a prescribed and the discovered process models, and to reuse the model for a better productivity and quality of the products.

Intentional Process Mining: Discovering and Modeling the Goals Behind Processes using Supervised Learning

The paper presents the Supervised Map Miner Method and reports two controlled experiments that were undertaken to evaluate precision, recall and F-Score and the results are promising since the authors were able to find the intentions underlying the activities as well as the corresponding map process model with satisfying accuracy, efficiency and performance.

What Requirements Engineering can Learn from Process Mining

  • Mahdi Ghasemi
  • Computer Science
    2018 1st International Workshop on Learning from other Disciplines for Requirements Engineering (D4RE)
  • 2018
How requirements engineering can benefit from process mining's components such as execution logs, process discovery and conformance techniques for requirements elicitation, prioritization and validation is highlighted.

Unsupervised discovery of intentional process models from event logs

A novel approach, so-called Map Miner Method (MMM), designed to automate the construction of intentional process models from process logs, which offers a new understanding of software processes, and could readily be used for recommender systems.



Process mining: Using CPN tools to create test logs for mining algorithms

CP-nets are extended to generate XML event logs that can be mined by process mining tools supporting this format and benefit from the simulation capabilities of CPN Tools and, therefore, avoid reinventing the wheel.

Process mining: a research agenda

Detecting Implicit Dependencies Between Tasks from Event Logs

This paper proposes three theorems to detect implicit dependency between tasks and gives their proofs, and the experimental results show that the approach is powerful enough to mine process models with non-free-choice constructs.

Genetic Process Mining

A genetic process mining approach using the so-called causal matrix as a representation for individuals is shown and it is shown that genetic algorithms can be used to discover Petri net models from event logs.

Process Mining - Discovery, Conformance and Enhancement of Business Processes

This book provides real-world techniques for monitoring and analyzing processes in real time and is a powerful new tool destined to play a key role in business process management.

Discovering colored Petri nets from event logs

This paper describes how the resulting model (including the discovered data dependencies) can be represented as a Colored Petri Net (CPN), and how further perspectives, such as the performance and organizational perspective, can be incorporated.

Contextual recommendations using intention mining on process traces: Doctoral consortium paper

  • G. Khodabandelou
  • Computer Science
    IEEE 7th International Conference on Research Challenges in Information Science (RCIS)
  • 2013
This thesis is to study process traces to propose recommendations to the actors by identifying a set of generic processes adaptable to the current actors' context and proposing recommendations to actors regarding to their context.

Mining Process Models from Workflow Logs

This work presents an approach for a system that constructs process models from logs of past, unstructured executions of the given process, and presents results from applying the algorithm to synthetic data sets as well as process logs obtained from an IBM Flowmark installation.

Mining Hierarchies of Models: From Abstract Views to Concrete Specifications

This work proposes an approach to process mining that combines novel discovery strategies with abstraction methods, with the aim of producing hierarchical views of the process that satisfactorily capture its behavior at different level of details.

Supervised intentional process models discovery using Hidden Markov models

The aim of this paper is to propose the use of probabilistic models to evaluate the most likely intentions behind traces of activities, namely Hidden Markov Models (HMMs).