Abstract
With the growing popularity of micro-task crowdsourcing platforms, new workflow-based micro-task crowdsourcing approaches are starting to emerge. Such workflows occur in legal, political and conflict resolution domains as well, presenting new challenges, namely in micro-task specification and human-machine interaction, which result mostly from the flow of unstructured data. Domain ontologies provide the structure and semantics required to describe the data flowing throughout the workflow in a way understandable to both humans and machines. This paper presents a method for the construction of micro-task workflows from legal domain ontologies. The method is currently being employed in the context of the UMCourt project in order to formulate information retrieval and conflict resolution workflows.
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Luz, N., Silva, N., Novais, P. (2014). A Method for Defining Human-Machine Micro-task Workflows for Gathering Legal Information. In: Casanovas, P., Pagallo, U., Palmirani, M., Sartor, G. (eds) AI Approaches to the Complexity of Legal Systems. AICOL 2013. Lecture Notes in Computer Science(), vol 8929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45960-7_20
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DOI: https://doi.org/10.1007/978-3-662-45960-7_20
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