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題名：結合鏈路預測和ET機器學習的科研合作推薦方法研究
書刊名：數據分析與知識發現
作者：呂偉民／王小梅／韓濤
出版日期：2017
卷期：2017(4)
頁次：38-45
主題關鍵詞：科研合作網絡；鏈路預測；機器學習；隨機森林；極端隨機樹；推薦；Scientific research collaboration network；Link prediction；Machine learning；Random forest；Extremely randomized trees；Recommendation
原始連結：連回原系統網址new window
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  • 被引用次數被引用次數:期刊(1) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:1
  • 共同引用共同引用:0
  • 點閱點閱:3
【目的】結合鏈路預測與機器學習,提出推薦未來科研合作的新方法,以提高單獨基于鏈路預測方法的推薦精確度。【方法】構建加權作者合作網,以不同的鏈路預測指標作為特征輸入,運用極端隨機樹(Extremely Randomized Trees,ET)機器學習算法訓練分類,并利用遍歷算法求取分類結果的最優權重組合,選取TOP準確度的預測作為合作推薦結果。【結果】選取納米科技領域2008年–2010年SCI論文數據進行實證。在城市合作推薦中,改進的ET方法優于已有方法,有良好的推薦成功率;預測方法受網絡結構等因素影響較小,適用范圍更廣泛。【局限】科研合作受合作動機、地域、語言等諸多因素影響,加權作者合作網沒有反映在一篇論文中同城市、同機構的多個作者,也沒有反映上述因素。【結論】改進算法能夠比單個預測指標產生更準確的合作推薦建議,也為推廣到大學等機構、個人等更微觀的應用層面提供參考。
[Objective] This paper proposes a method to recommend scientific research collaborators based on link prediction and machine learning, which improves the precision of traditional method. [Methods] First, we used Link Prediction Algorithm index to build the feature input, and adopted the Extremely Randomized Trees Algorithm to train the classifier. Then, we obtained the optimal weight combination with the traversal algorithm to combine the classification results linearly. Finally, we received the best recommendation of collaborators. [Results] The improved ET method had better performance than the existing ones in recommending the collaboration cities. Besides, the proposed method was less affected by factors such as the network structure, and could be used with more applications. [Limitations] Scientific research collaboration is affected by the cooperation motivation, geographical, language and many other factors. The weighted author network did not examine authors from the same cities or with the same organizations. [Conclusions] The propsoed method could produce better recommendation results, which might help universities, institutions and individuals identify academic collabortors.
期刊論文
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2.Newman, M. E. J.(2001)。The Structure of Scientific Collaboration Networks。Proceedings of the National Academy of Science，98(2)，404-409。  new window
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4.Hanley, J. A.、McNeil, B. J.(1982)。The meaning and use of the area under a receiver operating characteristic (ROC) curve。Radiology，143(1)，29-36。  new window
5.Herlocker, J. L.、Konstan, J. A.、Terveen, L. G.、Riedl, J. T.(2004)。Evaluating collaborative filtering recommender systems。ACM Transactions on Information Systems，22(1)，5-53。  new window
6.Barabási, A. L.、Jeong, H.、Ravasz, E.、Néda, Z.、Schubert, A.、Vicsek, T.(2002)。Evolution of the Social Network of Scientific Collaborations。Physica A: Statistical Mechanics and its Applications，311(3/4)，590-614。  new window
7.Newman, Mark E. J.(2001)。Scientific Collaboration Networks (II): Shortest Paths, Weighted Networks, and Centrality。Physical Review E: Statistical Nonlinear & Soft Matter Physics，64(1)，016132。  new window
8.Lu, L.、Zhou, T.(2011)。Link Prediction in Complex Networks: A Survey。Physica A: Statistical Mechanics and Its Applications，390(6)，1150-1170。  new window
9.Yan, E.、Guns, R.(2014)。Predicting and Recommending Collaborations: An Author-, Institution-, and Country-level Analysis。Journal of Informetrics，8(2)，295-309。  new window
10.張斌、馬費成(2015)。科學知識網絡中的鏈路預測研究述評。中國圖書館學報，41(3)，99-113。  延伸查詢new window
11.Zuckerman, H. A.(1968)。Patterns of Name Ordering Among Authors of Scientific Papers: A Study of Social Symbolism and Its Ambiguity。American Journal of Sociology，74(3)，276-291。  new window
12.Kretschmer, H.(2004)。Author Productivity and Geodesic Distance in Bibliographic Co-authorship Networks, and Visibility on the Web。Scientometrics，60(3)，409-420。  new window
13.Zhu, B.、Xia, Y.(2015)。An Information-theoretic Model for Link Prediction in Complex Networks。Scientific Reports，5，13707。  new window
14.Guns, R.、Rousseau, R.(2014)。Recommending Research Collaborations Using Link Prediction and Random Forest Classifiers。Scientometrics，101(2)，1461-1473。  new window
15.張斌、李亞婷(2016)。知識網絡演化模型研究述評。中國圖書館學報，42(5)，85-101。  延伸查詢new window
16.Liben-Nowell, D.、Kleinberg, J.(2007)。The Link Prediction Problem for Social Networks。Journal of the Association for Information Science and Technology，58(7)，1019-1031。  new window
17.呂琳媛(2010)。複雜網絡鏈路預測。電子科技大學學報，39(5)，651-661。  延伸查詢new window
18.Guns, R.(2009)。Generalizing Link Prediction: Collaboration at the University of Antwerp as a Case Study。Proceedings of the American Society for Information Science and Technology，46(1)，1-15。  new window
19.Arora, S. K.、Porter, A. L.、Youtie, J.(2013)。Capturing New Developments in an Emerging Technology: An Updated Search Strategy for Identifying Nanotechnology Research Outputs。Scientometrics，95(1)，351-370。  new window
20.Zhou, T.、Ren, J.、Medo, M.(2007)。Bipartite Network Projection and Personal Recommendation。Physical Review E，76(2)，046115。  new window
21.Schubert, T.、Sooryamoorthy, R.(2010)。Can the Centre-periphery Model Explain Patterns of International Scientific Collaboration Among Threshold and Industrialised Countries? The Case of South Africa and Germany。Scientometrics，83(1)，181-203。  new window
22.Boshoff, N.(2010)。South-South Research Collaboration of Countries in the Southern African Development Community (SADC)。Scientometrics，84(2)，481-503。  new window
23.Pedregosa, F.、Varoquaux, G.、Gramfort, A.、Michel, V.、Thirion, B.、Grisel, O.、Blondel, M.、Prettenhofer, P.、Weiss, R.、Dubourg, V.、Vanderplas, J.、Passos, A.、Cournapeau, D.、Brucher, M.、Perrot, M.、Duchesnay, É.(2011)。Scikit-learn: Machine Learning in Python。Journal of Machine Learning Research，12(85)，2825-2830。  new window
24.Adamic, L. A.、Adar, E.(2003)。Friends and neighbors on the web。Social Networks，25(3)，211-230。  new window
25.Getoor, L.、Diehl, C. P.(2005)。Link mining: A survey。ACM SIGKDD Explorations Newsletter，7(2)，3-12。  new window
會議論文
1.Guns, R.、Rousseau, R.(2013)。Predicting and Recommending Potential Research Collaborations1409-1418。  new window
2.Tylenda, T.、Angelova, R.、Bedathur, S.(2009)。Towards Time-aware Link Prediction in Evolving Social Networks。ACM。1-10。  new window
3.Wang, C.、Satuluri, V.、Parthasarathy, S.(2007)。Local Probabilistic Models for Link Prediction。Seventh IEEE International Conference on Data Mining, 2007。IEEE。322-331。  new window
4.Backstrom, L.、Leskovec, J.(2011)。Supervised Random Walks: Predicting and Recommending Links in Social Networks。ACM。635-644。  new window
5.Guns, R.(2011)。Bipartite Networks for Link Prediction: Can They Improve Prediction Performance249-260。  new window
6.Pavlov, M.、Ichise, R.(2007)。Finding Experts by Link Prediction in Co-authorship Networks。  new window
學位論文
1.Guns, R.(2012)。Missing Links: Predicting Interactions Based on a Multi-relational Network Structure with Applications in Informetrics(博士論文)。Universiteit Antwerpen。  new window
圖書
1.Mitchell, Tom M.(1997)。Machine Learning。The McGraw-Hill Companies, Inc.。  new window
2.De Solla Price, Derek J.(1986)。Little Science, Big Science...and Beyond。New York：Columbia University Press。  new window
3.Breiman, L.、Friedman, J. H.、Olshen, R. A.、Stone, C. J.(1984)。Classification and Regression Trees。CRC Press。  new window
圖書論文
1.Guns, R.(2014)。Link Prediction。Measuring Scholarly Impact。Springer International Publishing。  new window
 
 
 
 
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