Ontology: Core Process Mining and Querying Enabling Tool

Ontology permits the addition of semantics to process models derived from mining the various data stored in many information systems. The ontological schema enables for automated querying and inference of useful knowledge from the different domain processes. Indeed, such conceptualization methods particularly ontologies for process management which is currently allied to semantic process mining trails to combine process models with ontologies, and are increasingly gaining attention in recent years. In view of that, this chapter introduces an ontology-based mining approach that makes use of concepts within the extracted event logs about domain processes to propose a method which allows for effective querying and improved analysis of the resulting models through semantic labelling (annotation), semantic representation (ontology) and semantic reasoning (reasoner). The proposed method is a semantic-based process mining approach that is able to induce new knowledge based on previously unobserved behaviours, and a more intuitive and easy way to represent and query the datasets and the discovered models compared to other standard logical procedures. To this end, the study claims that it is possible to apply effective reasoning methods to make inferences over a process knowledge-base (e.g. the learning process) that leads to automated discovery of learning patterns and/or behaviour.

[1]  H. Lan,et al.  SWRL : A semantic Web rule language combining OWL and ruleML , 2004 .

[2]  Wil M. P. van der Aalst,et al.  Process querying: Enabling business intelligence through query-based process analytics , 2017, Decis. Support Syst..

[3]  D. Curtis Jamison,et al.  Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases , 2005, Journal of biomedicine & biotechnology.

[4]  Wil M. P. van der Aalst,et al.  Semantic Process Mining Tools: Core Building Blocks , 2008, ECIS.

[5]  Usman Naeem,et al.  Semantic-Based Model Analysis Towards Enhancing Information Values of Process Mining: Case Study of Learning Process Domain , 2016, SoCPaR.

[6]  Usman Naeem,et al.  Using semantic-based approach to manage perspectives of process mining: Application on improving learning process domain data , 2016, 2016 IEEE International Conference on Big Data (Big Data).

[7]  Hamish Cunningham,et al.  Information Extraction, Automatic , 2006 .

[8]  Maurizio Lenzerini,et al.  Using Ontologies for Semantic Data Integration , 2018, A Comprehensive Guide Through the Italian Database Research.

[9]  Usman Naeem,et al.  Discovery and Enhancement of Learning Model Analysis through Semantic Process Mining , 2016, CISIM 2016.

[10]  Bernhard Bauer,et al.  Process mining for semantic business process modeling , 2009, 2009 13th Enterprise Distributed Object Computing Conference Workshops.

[11]  Ingo Weber,et al.  User-Friendly Semantic Annotation in Business Process Modeling , 2007, WISE Workshops.

[12]  Silvana Quaglini,et al.  Knowledge-Based Trace Abstraction for Semantic Process Mining , 2017, AIME.

[13]  Hazalina Hashim Ontological structure representation in reusing ODL learning resources , 2016 .

[14]  Diego Calvanese,et al.  Ontology-Driven Extraction of Event Logs from Relational Databases , 2015, Business Process Management Workshops.

[15]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[16]  Sergio Greco,et al.  A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years , 2018, Studies in Big Data.

[17]  Andreas Abecker,et al.  Ontologies and the Semantic Web , 2011, Handbook of Semantic Web Technologies.

[18]  Hao Wang,et al.  Semantic data mining: A survey of ontology-based approaches , 2015, Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015).

[19]  Wil M. P. van der Aalst,et al.  Process Mining , 2016, Springer Berlin Heidelberg.

[20]  Christopher D. Manning,et al.  Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..

[21]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[22]  Kumar Abhishek,et al.  Architecting and Designing of Semantic Web Based Application using the JENA and PROTÉGÉ – A Comprehensive Study , 2011 .

[23]  Maria-Florina Balcan,et al.  Exploiting Ontology Structures and Unlabeled Data for Learning , 2013, ICML.

[24]  Usman Naeem,et al.  A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis , 2015, NaBIC.