Merging event logs for process mining: A rule based merging method and rule suggestion algorithm

Merging event logs for process mining: A rule based merging method and rule suggestion algorithm

In an inter-organizational setting the manual construction of process models is challenging because the different people involved have to put together their partial knowledge about the overall process. Process mining, an automated technique to discover and analyze process models, can facilitate the construction of inter-organizational process models. This paper presents a technique to merge the...

TWINCLE : A Constrained Sequential Rule Mining Algorithm for Event Logs

Discovering workflow patterns in event-logs is important for many organizations to understand and optimize organizational processes. Although numerous algorithms have been proposed in the literature to discover patterns in sequences of symbols, most of them are inadequate to discover patterns in rich event-log data. In this paper, motivated by the analysis of patient pathways in the health doma...

Merging rule-based belief databases

The problem of revising a belief database is treated in many classical works. We will consider here the problem of merging two belief databases (BDBs for short) Ψ1 and Ψ2, operation that will be denoted byΨ1 Ψ2, and whose result will be a new BDB. Since belief not necessarily reflects the actual state of the world (as opposed to knowledge), both BDBs could be incompatible. The goal is to constr...

Rule Merging in a Rule-Based Arabic Stemmer

A Novel Method for Selecting the Supplier Based on Association Rule Mining

One of important problems in supply chains management is supplier selection. In a company, there are massive data from various departments so that extracting knowledge from the company’s data is too complicated. Many researchers have solved this problem by some methods like fuzzy set theory, goal programming, multi objective programming, the liner programming, mixed integer programming, analyti...