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Refining ranked retrieval results for legal discovery search through supervised rank aggregation

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dc.contributor.authorAlmquist, Brian
dc.contributor.authorSrinivasan, Padmini
dc.date.accessioned2020-07-24
dc.date.accessioned2022-05-31T01:15:06Z
dc.date.available2022-05-31T01:15:06Z
dc.date.issued2013
dc.description.abstractWe propose and evaluate a data mining system that uses a set of document features describing each document in the context of partially evaluated ranked results. We find our system to be competitive with existing metasearch ranking strategies for prioritizing the review of evidence for legal relevance.
dc.format.extent81.68KB
dc.format.mimetypePDF
dc.identifier.citationAlmquist, B., & Srinivasan, P. (2013, October). Refining Ranked Retrieval Results for Legal Discovery Search Through Supervised Rank Aggregation. In Proceedings of the Annual Conference of CAIS/Actes du congrès annuel de l'ACSI.
dc.identifier.urihttps://hdl.handle.net/20.500.14078/1651
dc.languageEnglish
dc.language.isoen
dc.rightsAll Rights Reserved
dc.subjectinformation retrieval
dc.subjectrank aggregation
dc.titleRefining ranked retrieval results for legal discovery search through supervised rank aggregationen
dc.typePresentation
dspace.entity.type

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