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

Faculty Advisor

Date

2013

Keywords

information retrieval, rank aggregation

Abstract (summary)

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.

Publication Information

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.

DOI

Notes

Item Type

Presentation

Language

English

Rights

All Rights Reserved