The Use of Automatic Relevance feedback in Boolean Retrieval Systems
The Use of Automatic Relevance feedback in Boolean Retrieval Systems
复制标题
自动相关性反馈在布尔检索系统中的使用
DOI：
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发表时间：
1980
期刊：
影响因子：
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通讯作者：
James Desper
中科院分区：
文献类型：
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作者：
M. Dillon;James Desper
描述了一种用于布尔查询的自动重构的技术。基于初始检索的读者相关性判断，针对检索到的文档集中出现的反映术语在相关和非相关文档中的分布的术语导出流行度度量。这些措施，然后用于指导后续检索的布尔查询的建设。为了说明该技术，一系列的测试描述了它的应用程序在实验环境中的一个小数据库。结果与SMART型系统中采用的反馈相比毫不逊色。建议进行更广泛的测试以验证该技术。
A technique is described for automatic reformulation of boolean queries. Based on patron relevance judgements of an initial retrieval, prevalence measures are derived for terms appearing in the retrieved set of documents that reflect a term's distribution among the relevant and non‐relevant documents. These measures are then used to guide the construction of a boolean query for a subsequent retrieval. To illustrate the technique, a series of tests is described of its application to a small data base in an experimental environment. Results compare favourably with feedback as employed in a SMART‐type system. More extensive testing is suggested to validate the technique.