@conference {Choukri2021,
	title = {Context aware Hidden Markov Model for Intention process mining},
	booktitle = {5th International Conference on Intelligent Computing in Data Sciences, ICDS 2021},
	year = {2021},
	note = {cited By 0},
	abstract = {Nowadays, the omnipresence of digital devices and solutions in daily life made the digital footprints of individuals and the traces of their activities widely available. Smart devices generate a tremendous amount of data that and enables tracking their users{\textquoteright} activity. Extensive research has been conducted to produce generic process models based on the analysis of user{\textquoteright}s activity recorded during the enactment of operational processes. Unfortunately, these approaches considered only the relation between the observed activities and their sequences to infer the underlying process. Thus, ignoring the goal conditioning the user{\textquoteright}s behavior when triggering the actual process. Nevertheless, the same activity traces could serve to unhide the intention behind each process. This article will focus on presenting our approach to Contextual intention mining using Hidden Markov Model (HMM). This approach explores the close relationships between intention and context to construct the process model while ensuring consistency between observed context and actual intentions. {\textcopyright} 2021 IEEE.},
	keywords = {Behavioral research, Context, Data mining, Digital devices, Event logs, Goal mining, Goal models, Hidden Markov models, Information systems, Information use, Intention-oriented process modeling, Intentional process modeling, Machine learning, Markov modeling, Oriented process, Process Discovery, Process engineering, Process mining, Process recommendation, Process-aware information systems, Process-models, Supervised learning, Unsupervised learning, User profile},
	doi = {10.1109/ICDS53782.2021.9626765},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123483088\&doi=10.1109\%2fICDS53782.2021.9626765\&partnerID=40\&md5=d61fab7bfc96ede4658a8984da68ef3f},
	author = {Choukri, I. and Guermah, H. and Daosabah, A. and Nassar, M.}
}
@article {El-Bouroumi2021373,
	title = {Enhancing Business Process Modeling with Context and Ontology},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {12},
	number = {9},
	year = {2021},
	note = {cited By 0},
	pages = {373-380},
	abstract = {Business process is a sequence of events and tasks that encompass actions and people. Therefore, a company that pays much attention to its business processes has to clearly identify and define the procedures of their relations. However, with the exponential evolution in ubiquitous computing, the exploitation of information spread all over different devices has become essential to further improve business processes. Hence, inthis paper we present a new approach for business process modeling that is based on context-awareness and ontology. We propose a set of meta-model for the elements that we find very important, taking into account the context and, in modeling, the business process. To validate our approach, we propose a concrete case study about transport system to provide a proof of the applicability as well as the utility of the model {\textcopyright} 2021. International Journal of Advanced Computer Science and Applications. All Rights Reserved.},
	keywords = {Business Process, Business process modeling, Context, Context ontology, Context- awareness, Exponentials, Metamodeling, New approaches, Ontology, Ontology{\textquoteright}s, Process engineering, Sequence of events, Systems engineering, Ubiquitous computing},
	doi = {10.14569/IJACSA.2021.0120942},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119425334\&doi=10.14569\%2fIJACSA.2021.0120942\&partnerID=40\&md5=da72c57b36a3bdb00125409bd14820d1},
	author = {El-Bouroumi, J. and Guermah, H. and Nassar, M.}
}
