Rather than relying on automatically recorded hidden field data, extraction rules can be manually added and customized as needed.

提取规则可以根据需要手动添加和自定义，而不是依赖于自动记录的隐藏字段数据。

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Data mining is an information extraction activity whose goal is to discover hidden facts contained in databases.

数据挖掘是信息提取的活动，其目标是发现隐藏的事实数据库。

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This paper proposes a new algorithm using hidden Markov model for information extraction based on multiple templates due to the variety of training data.

针对训练数据来源的多样化，提出了基于多模板隐马尔可夫模型的文本信息抽取算法。

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