Name
Papers
Collaborators
DIOGO R. FERREIRA
43
116
Citations 
PageRank 
Referers 
539
35.43
1484
Referees 
References 
749
458
Search Limit
1001000
Title
Citations
PageRank
Year
Explainable deep learning for the analysis of MHD spectrograms in nuclear fusion00.342022
How Much Does Stock Prediction Improve with Sentiment Analysis?00.342020
A Survey of Process Mining Competitions - The BPI Challenges 2011-2018.00.342019
Assessing Agile Software Development Processes with Process Mining: A Case Study10.482018
Applications of Deep Learning to Nuclear Fusion Research.00.342018
A Rule-Based Approach to the Implementation of Business Processes in Normalized Systems00.342016
Parallelization of Transition Counting for Process Mining on Multi-core CPUs and GPUs.00.342016
Improving process models by mining mappings of low-level events to high-level activities40.412014
A DSL for specifying run-time adaptations for embedded systems: an application to vehicle stereo navigation00.342014
Specifying Dynamic Adaptations for Embedded Applications Using a DSL00.342014
Specifying Adaptations through a DSL with an Application to Mobile Robot Navigation.50.502013
Proceedings of the 3rd Business Process Intelligence Challenge co-located with 9th International Business Process Intelligence Workshop (BPI 2013), Beijing, China, August 26, 2013.123.052013
Report: Business Process Intelligence Challenge 2013.00.342013
Mining the low-level behaviour of agents in high-level business processes50.502013
Using Inductive Reasoning to Find the Cause of Process Delays30.412013
Improving Business Process Models with Agent-Based Simulation and Process Mining.40.442013
THE IMPACT OF SEARCH DEPTH ON CHESS PLAYING STRENGTH00.342013
Business process analysis in healthcare environments: A methodology based on process mining1154.152012
A semantic approach to the discovery of workflow activity patterns in event logs50.452012
A Hierarchical Markov Model to Understand the Behaviour of Agents in Business Processes.30.402012
Performance Analysis Of Healthcare Processes Through Process Mining10.382012
Determining the Strength of Chess Players Based on Actual Play.10.372012
Securely Storing and Executing Business Processes in the Cloud.00.342012
Ontology-Based Discovery of Workflow Activity Patterns.40.412011
Process Mining Manifesto.191.092011
Sequence partitioning for process mining with unlabeled event logs60.772011
Discovering User Communities in Large Event Logs.50.532011
A Domain-Specific Language for the Specification of Adaptable Context Inference40.452011
Providing user context for mobile and social networking applications240.922010
Preprocessing techniques for context recognition from accelerometer data1546.362010
Context Inference for Mobile Applications in the UPCASE Project130.752009
Estimating the Parameters of Randomly Interleaved Markov Models40.592009
Mobile Context Provider for Social Networking00.342009
Understanding Spaghetti Models with Sequence Clustering for ProM421.682009
Discovering Process Models from Unlabelled Event Logs481.802009
Automatic Extraction of Process Control Flow from I/O Operations50.462008
An Integrated Life Cycle For Workflow Management Based On Learning And Planning381.542006
On the concurrency of inter-organizational business processes00.342006
Towards a workflow-based integration architecture for business networking40.492005
Learning, planning, and the life cycle of workflow management20.362005
Building An E-Marketplace On A Peer-To-Peer Infrastructure20.412004
Developing a reusable workflow engine60.552004
Building a Workflow Enactment Service for Telework Co-Ordination.00.341999