使用奇异值分解的基于Web的集合选择

Johnny King, Yuefeng Li
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引用次数: 11

摘要

随着Internet上可用的电子数据集合数量的增加,为给定查询找到正确集合的难度也在增加。通常,第一次使用的用户会被可用的选项数组所淹没,并且会浪费时间在集合名称的页面中搜索,然后在进行临时搜索后阅读结果页面。自动集合选择方法通过根据查询建议搜索集合的最佳子集来尝试解决这个问题。这对于包含大量频繁变化的电子馆藏和不能使用蜘蛛等传统方法完全索引的馆藏的字段非常重要。我们提出了一种选择最佳集合并减少需要搜索的集合数量的解决方案。在Web搜索引擎上对该系统进行的初步测试表明,这解决了许多基于Web的集合选择问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web based collection selection using singular value decomposition
As the number of electronic data collections available on the Internet increases, so does the difficulty of finding the right collection for a given query. Often the first time user is overwhelmed by the array of options available, and wastes time hunting through pages of collection names, followed by time reading results pages after doing an ad-hoc search. Automatic collection selection methods try to solve this problem by suggesting the best subset of collections to search based on a query. This is of importance to fields containing large number of electronic collections, which undergo frequent change, and collections that cannot be fully indexed using traditional methods such as spiders. We present a solution to this problem of selecting the best collections and reducing the number of collections needing to be searched. Preliminary tests of the system, conducted on Web search engines, suggest that this solves much of the Web based Collection selection problem.
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