计算机科学
关键词提取
耙
水准点(测量)
概括性
情报检索
领域(数学分析)
自然语言处理
精确性和召回率
词汇
人工智能
数据挖掘
数学分析
心理治疗师
地理
哲学
大地测量学
工程类
机械工程
语言学
数学
心理学
作者
Stuart Rose,Dave Engel,Nick Cramer,Wendy Cowley
标识
DOI:10.1002/9780470689646.ch1
摘要
Keywords are widely used to define queries within information retrieval (IR) systems as they are easy to define, revise, remember, and share. This chapter describes the rapid automatic keyword extraction (RAKE), an unsupervised, domain-independent, and language-independent method for extracting keywords from individual documents. It provides details of the algorithm and its configuration parameters, and present results on a benchmark dataset of technical abstracts, showing that RAKE is more computationally efficient than TextRank while achieving higher precision and comparable recall scores. The chapter then describes a novel method for generating stoplists, which is used to configure RAKE for specific domains and corpora. Finally, it applies RAKE to a corpus of news articles and defines metrics for evaluating the exclusivity, essentiality, and generality of extracted keywords, enabling a system to identify keywords that are essential or general to documents in the absence of manual annotations. Controlled Vocabulary Terms benchmark polls
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