Query Expansion for Noisy Legal Documents

17th Text REtrieval Conference

图书情报档案学

Lidan Wang1,3 and Douglas W. Oard2,3

PID  :  126348

学科分类：社会科学、人文和艺术（综合）

来源: CEUR

【 摘 要 】

The vocabulary of the TREC Legal OCR collection is noisy and huge. Standard techniques for im proving retrieval performance such as contentbased query expansion are ineffective for such document collection. In our work, we focused on exploiting metadata using blind relevance feedback, iterative improvement from the reference Boolean run, and the effects of using terms from different topic fields