Information Access Based on Associative Calculation
Information Access Based on Associative Calculation
复制标题
基于联想计算的信息获取
DOI：
--
复制
发表时间：
2000
期刊：
影响因子：
--
通讯作者：
Hirofumi Sakurai
中科院分区：
文献类型：
--
作者：
Akihiko Takano;Yoshiki Niwa;Shingo Nishioka;Makoto Iwayama;Toru Hisamitsu;Osamu Imaichi;Hirofumi Sakurai
文本相似性的统计度量在文本信息检索中已经广泛应用了几十年。它们是提高信息检索系统有效性的基础，包括检索、聚类和摘要。我们开发了一个信息检索系统DualNAVI，它为用户提供了丰富的交互在文档空间和词空间。我们表明，关联计算测量文档或单词之间的相似性是这种有效的信息访问与DualNAVI的计算基础。本文还讨论了文档聚类（层次贝叶斯聚类）和术语代表性度量（基线方法）的新方法。两者都有坚实的数学基础，基本上依赖于联想计算。
The statistical measures for similarity have been widely used in textual information retrieval for many decades. They are the basis to improve the effectiveness of IR systems, including retrieval, clustering, and summarization. We have developed an information retrieval system DualNAVI which provides users with rich interaction both in document space and in word space. We show that associative calculation for measuring similarity among documents or words is the computational basis of this effective information access with DualNAVI. The new approaches in document clustering (Hierarchical Bayesian Clustering), and measuring term representativeness (Baseline method) are also discussed. Both have sound mathematical basis and depend essentially on associative calculation.