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Novelty and Redundancy Detection in Adaptive Filtering

机译:自适应滤波中的新颖性和冗余检测

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This paper addresses the problem of extending an adaptive information filtering system to make decisions about the novelty and redundancy of relevant documents. It argues that relevance and redundance should each be modelled explicitly and separately. A set of five redundancy measures are proposed and evaluated in experiments with and without redundancy thresholds. The experimental results demonstrate that the cosine similarity metric and a redundancy measure based on a mixture of language models are both effective for identifying redundant documents.
机译:本文解决了扩展自适应信息过滤系统的问题,以决策相关文档的新颖性和冗余。它争辩说,每个都应明确和分开建模相关性和冗余。提出了一组五种冗余度量,并在实验中进行了评估,无冗余阈值。实验结果表明,基于语言模型的混合的余弦相似度指标和冗余度量既有效地识别冗余文档。

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