Web process and workflow path mining using the Multimethod approach

Cardoso, Jorge; Lenic, Mitja

doi:10.1504/ijbidm.2006.009137

Cited by 18 publications

(7 citation statements)

References 26 publications

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“…This information enables the analyst to obtain more insight into the process execution and its environment and react if an adaptation or exceptional interference becomes necessary, reallocation of resources. Examples of these analyses are what-if analysis [12], performance monitoring [16], performance prediction [38], path prediction [6], sensitivity analysis [11], and bottleneck detection [41]. Traditionally, in the BPM domain two basic types of analysis techniques are utilised to extract additional information from low-level data, i.e.…”

Section: Analysis Types For Reasoning On Bpm@rtmentioning

confidence: 99%

Research Challenges for Business Process Models at Run-Time

et al. 2014

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Abstract. Today's fast and competitive markets require businesses to react faster to changes in its environment, and sometimes even before the changes actually happen. Changes can occur on almost every level, e.g. change in demand of customers, change of law, or change of the corporate strategy. Not adapting to these changes can result in financial and legal consequences for any business organisation. IT-controlled business processes are essential parts of modern organisations which motivates why business processes are required to efficiently adapt to these changes in a quick and flexible way. This requirement suggests a more dynamic handling of business processes and their models, moving from design-time business process models to run-time business process models. One general approach to address this problem is provided by the community of models@run.time, in which models reflect the system's current state at any point in time and allow immediate reasoning and adaptation mechanisms. This paper examines the potential role of business process models at run-time by: (1) discussing the state-of the art of both, business process modelling and models@run.time, (2) reflecting on the nature of business processes at run-time, and (3) most importantly, highlighting key research challenges that need addressing to make this step.

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Section: Analysis Types For Reasoning On Bpm@rtmentioning

confidence: 99%

Research Challenges for Business Process Models at Run-Time

et al. 2014

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“…It is worth mentioning further methods that in some cases can extract relevant knowledge from much less specific data. For example there is the analysis of electronic trails (e.g., Web server log files or exchanges of e-mail) (Cardoso and Lenic 2006) as well as the analysis of social networks.…”

Section: Knowledge Acquisitionmentioning

confidence: 99%

“…In recent years some of the major processes of the process management life cycle such as process analysis (Biazzo, 2000), process design (Cousins and Stewart, 2002), and process measurement (Cardoso et al, 2006) are reaching, from the companies' point of view, a satisfying level of maturity, on the other hand deficiencies become apparent when processes are actually implemented (BPM Study, 2006). In other words, in spite of all business process approaches, methodologies, models, standards, which in specific contexts and different focuses address BPM and improvement of business processes, there is still a large gap between "theory" -how an organization wants to function, and working practice -what actually happens in business process execution.…”

Section: Introductionmentioning

confidence: 99%

The Business Process Knowledge Framework

Hrastnik

Cardoso

Kappe³

2007

Proceedings of the Ninth International Conference on Enterprise Information Systems

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Organizations today are confronted with huge problems regarding following and implementing their own business process models. On the one hand, due to a lack of planning and requirements analysis, process models are often unfeasible or difficult to execute in practice. On the other hand, process designers often ignore the importance of studying the different roles and their perspectives on a business process when constructing a process model. This leads to the deployment of process models that do not "satisfy" process stakeholders. This paper addresses those two problems and proposes a business process knowledge framework as a possible solution. Our framework for business process knowledge management integrates three elements that we consider fundamental to correctly model business processes: stakeholders' perspectives, knowledge types and views. It is shown how the business process framework can contribute to the improvement of the process knowledge acquisition phase of process design, and how it can support process knowledge communication to stakeholders. Finally, we argue that the latest developments in the Semantic Web are an interesting solution to support the integration of information and knowledge represented within our framework.

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“…In this regard, the web usage recommender mechanisms deploy the web server logs as input, and effectively exploit the data mining approaches like the association rules and clustering to extort the navigational models, which can be subsequently employed to offer the promotions. The web server logs document the user browsing history, consisting of the extremely concealed data on the users and their navigation (Simon, 2002;Cardoso and Lenic, 2006). With the result, they effectively highlight themselves as the excellent candidates for the purpose of unambiguous user rating or as Feedback in developing user models.…”

Section: Introductionmentioning

confidence: 99%

Personalised e-learning system using learner profile ontology and sequential pattern mining-based recommendation

Muruganandam

Srininvasan

2017

IJBIDM

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Abstract:The ever-zooming issue of personalisation in the domain of the e-learning or the adaptive e-learning has emerged as a hot subject of intriguing debate among the inquisitive investigators in the last few years. In the learning contents module, all the critical learning materials in the shape of text, video or audio are collected and saved by means of the data management approach so as to effectively orchestrate the entire learning material. In the profile ontology module, the learner profile is saved as the ontology with a clear-cut framework and data. The Markov model is also utilised in this regard. In the instructor module, the online tutoring for each and every learner in accordance with the protocol devised by means of the captioned techniques is carried out. The execution is performed through the JAVA programming and protégé device and the performance is subjected to assessment.Keywords: e-learning; prefix-span algorithm; graphical user interface; dataset description.Reference to this paper should be made as follows: Muruganandam, S. and Srininvasan, N. (2017) 'Personalised e-learning system using learner profile ontology and sequential pattern mining-based recommendation', Int.

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Web process and workflow path mining using the Multimethod approach

Cited by 18 publications

References 26 publications

Research Challenges for Business Process Models at Run-Time

Research Challenges for Business Process Models at Run-Time

The Business Process Knowledge Framework

Personalised e-learning system using learner profile ontology and sequential pattern mining-based recommendation

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