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Proposal of square metrics for measuring Business Process Model complexity
This work proposes simple yet practical square metrics for describing complexity of a BP model that are easy to interpret and provide some basic information about the structural complexity of the model.
Application of Bayesian Networks to Recommendations in Business Process Modeling
This paper proposes a method that uses Bayesian Networks for recommendation purposes in process modeling that uses configurable business processes that combine a set of reference models.
Towards the Development of Sensor Platform for Processing Physiological Data from Wearable Sensors
Critical comparison of quality of HR and GSR signals leads to the conclusion that future works should focus on the BITalino, possibly combined with the MS Band 2 in some cases.
SBVRwiki a Web-Based Tool for Authoring of Business Rules
In the paper, a new tool called SBVRwiki is proposed. It is an online collaborative solution that allows for distributed and incremental SBVR rule authoring for business analytics and users. It uses
Overview of Recommendation Techniques in Business Process Modeling
This paper presents several machine learning methods which can be used for recommending features of business process models and introduces a categorization and examples of recommendation approaches.
Collective Knowledge Engineering with Semantic Wikis
The paper discusses a new semantic wiki architecture called PlWiki, which aims to provide a strong knowledge representation and reasoning with Horn clauses-based representation and an extension to already available flexible wiki solution (DokuWiki) instead of modifying existing wiki engine.
Formal Model of Business Processes Integrated with Business Rules
The paper presents a formal description of the integration of Business Processes with Business Rules and provides a general model for such integration as well as the model applied to a specific rule representation from the Semantic Knowledge Engineering approach.
Rules Verification and Validation
The aim is to show how the quality of rules can be improved or kept at a relatively high level, even in environments with numerous active rules.
Knowledge Representation with Granular Attributive Logic for XTT-Based Expert Systems
In the proposed logic set values are allowed and various relational symbols are used to form atomic formulae and the proposed language provides a concise and elegant tool for design, implementation and verification of rule-based systems.