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

Author
Almquist, Brian
Srinivasan, Padmini
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