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A Research on Network Similarity Search Algorithm for Biological Networks

机译:生物网络网络相似性搜索算法研究

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摘要

The biological network database presents exponential growth, how to find the target network accurately from the network database becomes the difficult problem. This paper proposes a new network similarity search algorithm, the similar network of Top k is calculated by two methods, the similar networks returned by the two algorithms are then filtered by overlap fractions, the weighted reordering algorithm is used to reorder the two sets of data, a precise set of similar network data sets is returned finally.In this paper, the accuracy of the query is judged by the comparison of the edge correctness (EC) value and the maximum public connection subgraph (LCCS) value of the returned sorted similar network data set, and compare query time with other algorithms.From the results, this algorithm is superior to other algorithms in query accuracy and query speed.
机译:生物网络数据库提出指数增长,如何从网络数据库中准确地找到目标网络成为困难问题。本文提出了一种新的网络相似性搜索算法,通过两种方法计算类似的顶部K网络,然后通过重叠分数滤除两个算法返回的类似网络,加权重新排序算法用于重新排序两组数据,最后返回精确的类似网络数据集。在本文中,通过比较边缘正确性(EC)值和返回的最大公共连接子图(LCCS)值来判断查询的准确性。网络数据集,并将查询时间与其他算法进行比较。从结果中,该算法优于查询精度和查询速度的其他算法。

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