RT Journal Article SR Electronic T1 Ontology-based workflow extraction from texts using word sense disambiguation JF bioRxiv FD Cold Spring Harbor Laboratory SP 082784 DO 10.1101/082784 A1 Ahmed Halioui A1 Petko Valtchev A1 Abdoulaye Baniré Diallo YR 2016 UL http://biorxiv.org/content/early/2016/10/24/082784.abstract AB This paper introduces a method for automatic workflow extraction from texts using Process-Oriented Case-Based Reasoning (POCBR). While the current workflow management systems implement mostly different complicated graphical tasks based on advanced distributed solutions (e.g. cloud computing and grid computation), workflow knowledge acquisition from texts using case-based reasoning represents more expressive and semantic cases representations. We propose in this context, an ontology-based workflow extraction framework to acquire processual knowledge from texts. Our methodology extends classic NLP techniques to extract and disambiguate tasks in texts. Using a graph-based representation of workflows and a domain ontology, our extraction process uses a context-based approach to recognize workflow components : data and control flows. We applied our framework in a technical domain in bioinformatics : i.e. phylogenetic analyses. An evaluation based on workflow semantic similarities on a gold standard proves that our approach provides promising results in the process extraction domain. Both data and implementation of our framework are available in : http://labo.bioinfo.uqam.ca/tgrowler.