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Internet information source discovery based on multi-seeds cocitation

机译:基于多种子引用的互联网信息源发现

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The technology of Internet information source discovery on specific topic is the groundwork of information acquisition in current big data era. This paper presents a multi-seeds cocitation algorithm to find new Internet information sources. The proposed algorithm is based on cocitation, but what difference with the traditional algorithms is that we use multiple websites on specific topic as input seeds. Then we induce Combined Cocitation Degree(CCD) to measure the relevancy of newly found websites, which is that the new websites have higher combined cocitation degree and are more topic related. Finally a websites collection of the biggest CCD is referred to as the new Internet information sources on the specific topic. The experiments show that the proposed method outperforms traditional algorithms in the scenarios we tested.
机译:特定主题的Internet信息源发现技术是当前大数据时代信息获取的基础。本文提出了一种多种子引用算法,以查找新的Internet信息源。提出的算法是基于引用的,但是与传统算法的不同之处在于我们使用特定主题的多个网站作为输入种子。然后通过归纳联合引用度(CCD)来衡量新发现网站的相关性,即新网站具有更高的联合引用度,并且与主题相关性更高。最后,最大的CCD网站集被称为特定主题的新Internet信息源。实验表明,在我们测试的场景中,该方法优于传统算法。

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