期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2010
卷号：2010
出版社：ACL Anthology
摘要：Current work on automatic opinion mining
has ignored opinion targets expressed
by anaphorical pronouns, thereby missing
a significant number of opinion targets. In
this paper we empirically evaluate whether
using an off-the-shelf anaphora resolution
algorithm can improve the performance of
a baseline opinion mining system. We
present an analysis based on two different
anaphora resolution systems. Our experiments
on a movie review corpus demonstrate,
that an unsupervised anaphora resolution
algorithm significantly improves the
opinion target extraction. We furthermore
suggest domain and task specific extensions
to an off-the-shelf algorithm which
in turn yield significant improvements.
