The Factors Affecting the Performance of Data Fusion Algorithms

M. Nassar, G. Kanaan
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引用次数: 7

Abstract

The enormous amount of data which is distributed on the World Wide Web can be very useful if the users became able to get these data in an easy and appropriate method, search engines help the users to find what they need from this enormous amount of data. Meta-search is the application of data fusion to document retrieval, Metasearch engine takes as an input the N ranked lists output by each of N search engines in response to a given query, As output, it computes a single ranked list, which is hopefully an improvement over any input list as measured by standard information retrieval performance metrics such as the mean average precision (MAP). Our goal in this paper is to answer the following question, what are the factors affecting the performance of Data fusion algorithms? The reason behind introducing those factors is the absence of a single source in the literature able to present all those factors in an organized and complete manner. This work is needed to integrate all data fusion performance research findings. This paper contributes to the data fusion literature by two things, firstly; it will deliver all factors affecting the performance of data fusion algorithms in an organized and complete manner. Secondly; it will deliver recommendations which are related to how and when to deal with the factors that affect the performance.
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影响数据融合算法性能的因素
如果用户能够以一种简单而适当的方法获得这些数据,那么分布在万维网上的大量数据将非常有用,搜索引擎可以帮助用户从这些大量数据中找到他们需要的东西。元搜索是数据融合在文档检索中的应用,元搜索引擎将N个搜索引擎中每个搜索引擎对给定查询的N个排序列表作为输入,作为输出,它计算单个排序列表,这比任何输入列表都有改进,可以通过标准信息检索性能指标如平均精度(MAP)来衡量。我们在本文中的目标是回答以下问题,影响数据融合算法性能的因素是什么?引入这些因素背后的原因是在文献中缺乏一个单一的来源,能够以有组织和完整的方式呈现所有这些因素。这项工作需要整合所有数据融合性能的研究成果。本文对数据融合文献的贡献主要体现在两个方面:一是数据融合;它将有组织、完整地传递影响数据融合算法性能的所有因素。其次;它将提供有关如何以及何时处理影响绩效的因素的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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