Using latent semantic indexing for literature based discovery

被引:1
作者
Gordon, MD [1 ]
Dumais, S
机构
[1] Univ Michigan, Sch Business, Ann Arbor, MI 48109 USA
[2] Microsoft Corp, Res, Redmond, WA 98052 USA
来源
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE | 1998年 / 49卷 / 08期
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Latent semantic indexing (LSI) is a statistical technique for improving information retrieval effectiveness. Here, we use LSI to assist in literature-based discoveries. The idea behind literature-based discoveries is that different authors have already published certain underlying scientific ideas that, when taken together, can be connected to hypothesize a new discovery, and that these connections can be made by exploring the scientific literature. We explore latent semantic indexing's effectiveness on two discovery processes: uncovering "nearby" relationships that are necessary to initiate the literature based discovery process; and discovering more distant relationships that may genuinely generate new discovery hypotheses.
引用
收藏
页码:674 / 685
页数:12
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