WEIRD: an approach to concept-based information retrieval
WEIRD: an approach to concept-based information retrieval
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WEIRD：一种基于概念的信息检索方法
DOI：
10.1145/1095366.1095368
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发表时间：
1978
期刊：
影响因子：
--
通讯作者：
Matthew B. Koll
中科院分区：
文献类型：
--
作者：
Matthew B. Koll
Dogar是锡拉丘兹大学设计并实现的一个自动文档检索系统，它试图将计算机检索的艺术从单词匹配提升到判断概念相似性。Order使用向量空间模型来表示术语和文档之间的关系。空间中的项是根据它们的“意义”来定位的，“意义”是它们与数据库中所有其他项的接近程度，通过共现频率来衡量。这是在不操作大型矩阵的情况下完成的。空间的尺寸不用于定义关系；项目仅由其相对于其他项目的位置来定义。检索由与绘制的查询的欧几里得距离确定。在论文的第一部分，描述了怪诞的基本特征。第二，报告了初步评估的结果。然后考虑进一步开发怪异的替代方案。
WEIRD is an automatic document retrieval system designed and implemented at Syracuse University, which attempts to advance the art of computerized retrieval from word-matching to judging conceptual similarity. WEIRD uses a vector space model to represent the relations among terms and documents. Items in the space are located according to their "meaning", which is their proximity to all other items in the data base as measured by co-occurrence frequencies. This is done without manipulating large matrices. The dimensions of the space are not used to define relations; items are defined solely by their position relative to the other items. Retrieval is determined by Euclidean distance from the plotted query. In the first section of the paper the basic characteristics of WEIRD are described. Second, the results of a preliminary evaluation are reported. Alternatives for further development of WEIRD are then considered.