Refining ranked retrieval results for legal discovery search through supervised rank aggregation
information retrieval, rank aggregation
We 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.
Almquist, 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.
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