منابع مشابه
Discovering Constraints for Inductive Process Modeling
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combinations of these components. Previous research on inductive process modeling, which constructs models from knowledge and time-series data, has relied on handcrafted constraints. In this paper, we report an approach to ...
متن کاملCross-Domain Transfer of Constraints for Inductive Process Modeling
In this paper, we discuss a mechanism for transfer learning in the context of inductive process modeling. We begin by describing the dual role of knowledge as a source of model components and structural constraints. Next, we review the task of inductive process modeling and emphasize the effect of domain knowledge on the learning component. We then describe the performance and learning elements...
متن کاملProcess Discovery using Inductive Miner and Decomposition
This report presents a submission to the Process Discovery Contest [1]. The contest is dedicated to the assessment of tools and techniques that discover business process models from event logs. The objective is to compare the efficiency of techniques to discover process models that provide a proper balance between “overfitting” and “underfitting”. In the context of the Process Discovery Contest...
متن کاملInductive Revision of Quantitative Process Models
Most research on computational scientific discovery has focused on developing an initial model, but an equally important task involves revising a model in response to new data. In this paper, we present an approach that represents candidate models as sets of quantitative processes and that treats revision as search through a model space which is guided by time-series observations and constraine...
متن کاملRevising Process Models through Inductive Learning
Discovering the Business Process (BP) model underpinning existing practices through analysis of event logs, allows users to understand, analyse and modify the process. But, to be useful, the BP model must be kept in line with practice throughout its lifetime, as changes occur to the business objectives, technologies and quality programs. Current techniques require users to manually revise the B...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2007
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-007-5042-6