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Hilltop Based Recommendation in Co-author Networks

机译:合著者网络中基于Hilltop的推荐

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摘要

The scale of projects and literatures have been continuously expanded and become more complex with the development of scientific research. Scientific cooperation has become an important trend in the scientific research. Analysis of the co-author network is a big data problem. Without enough data mining, the research cooperation will be limited to some same group, named as 'small group' in the co-author networks. This situation has led to the researchers' lack of openness and limited scientific research results. It is important to recommend some potential collaboration from huge amount of literature. We propose a method based on Hilltop algorithm, an algorithm in search engine, to recommend co-authors by link analysis. The candidate set is screening and scored for recommendation. By setting certain rules, the expert set formation of the Hilltop algorithm is added to the screening. And the score is calculated by the durations and times of the collaborations. The co-authors can be extracted and recommended from the big data of the scientific research literatures through the experiments.
机译:随着科学研究的发展,项目和文献的规模不断扩大,变得越来越复杂。科学合作已成为科学研究的重要趋势。共同作者网络的分析是一个大数据问题。如果没有足够的数据挖掘,则研究合作将仅限于同一组,在共同作者网络中被称为“小组”。这种情况导致研究人员缺乏开放性,科研成果有限。从大量文献中建议一些潜在的合作很重要。我们提出一种基于Hilltop算法(搜索引擎中的算法)的方法,以通过链接分析推荐合作者。筛选候选集并评分以推荐。通过设置某些规则,将Hilltop算法的专家集形式添加到筛选中。分数由合作的持续时间和时间计算得出。通过实验可以从科学研究文献的大数据中提取并推荐合著者。

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