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Disproving the fusion hypothesis

机译:驳斥融合假设

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Many prior efforts have been devoted to the basic idea that data fusion techniques can improve retrieval effectiveness. Recent work in the area suggests that many approaches, particularly multiple-evidence combinations, can be a successful means of improving the effectiveness of a system. Unfortunately, the conditions favorable to effectiveness improvements have not been made clear. We examine popular data fusion techniques designed to achieve improvements in effectiveness and clarify the conditions required for data fusion to show improvement. We demonstrate that for fusion to improve effectiveness, the result sets being fused must contain a significant number of unique relevant documents. Furthermore, we show that for this improvement to be visible, these unique relevant documents must be highly ranked. In addition, we present a comprehensive discussion on why previous assumptions about the effectiveness of multiple-evidence techniques are misleading. Detailed empirical results and analysis areprovided to support our conclusions.
机译:已经有许多先前的努力致力于数据融合技术可以提高检索效率的基本思想。该领域的最新工作表明,许多方法,尤其是多证据组合,可以成为提高系统有效性的成功手段。不幸的是,尚未明确有利于提高效率的条件。我们研究了旨在提高有效性的流行数据融合技术,并阐明了数据融合以显示出改进所需要的条件。我们证明,为了提高融合效果,要融合的结果集必须包含大量独特的相关文档。此外,我们表明,要使这种改进可见,这些独特的相关文档必须进行高度排名。此外,我们就为何对多证据技术的有效性的先前假设产生误导的原因进行了全面的讨论。提供了详细的经验结果和分析以支持我们的结论。

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