Abstract
This paper highlights the benefit of semantic information retrieval in legal networks. User queries get more complex when they combine constraints on semantic content and intertextual links between documents. Comparing two methods of search in legal collection networks, we present new functionalities of search and browsing. Relying on a structured representation of the collection graph, the first approach allows for approximate answers and knowledge discovery. The second one supports richer semantics and scalability but offers fewer search functionalities. We indicate how those approaches could be combined to get the best of both.
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The target scale is a few hundred documents, but we must further optimize the code for it (solutions exist, it is an implementation issue).
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Acknowledgments
This work has been partially funded by French Single Inter-Ministry Fund (FUI-9, 2010–2013) and is supported by the Labex EFL supported by the French National Research Agency (ANR-10-LABX-0083).
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Mimouni, N., Nazarenko, A., Salotti, S. (2018). Answering Complex Queries on Legal Networks: A Direct and a Structured IR Approaches. In: Pagallo, U., Palmirani, M., Casanovas, P., Sartor, G., Villata, S. (eds) AI Approaches to the Complexity of Legal Systems. AICOL AICOL AICOL AICOL AICOL 2015 2016 2016 2017 2017. Lecture Notes in Computer Science(), vol 10791. Springer, Cham. https://doi.org/10.1007/978-3-030-00178-0_31
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