Advances in computational intelligence最新文献_第9页

Collaborator recommendation integrating author’s cooperation strength and research interests on attributed graph 基于作者合作实力和研究兴趣的属性图合作者推荐

Advances in computational intelligence Pub Date : 2021-05-31 DOI: 10.1007/s43674-021-00002-y

Donglin Hu, Huifang Ma

{"title":"Collaborator recommendation integrating author’s cooperation strength and research interests on attributed graph","authors":"Donglin Hu, Huifang Ma","doi":"10.1007/s43674-021-00002-y","DOIUrl":"10.1007/s43674-021-00002-y","url":null,"abstract":"<div><p>Collaborator recommendation aims to seek suitable collaborators for a given author. In this paper, we model all authors and their features as an attributed graph, and then perform community search on the attributed graph to locate the best collaborator community. From the early collaborative filtering-based methods to the recent deep learning-based methods, most existing works usually unilaterally weigh the network structure or node attributes, or directly search the community via the given node. We argue that the inherent disadvantage of these methods is that the quality of the node to be recommended may not be high, which can lead to suboptimal recommendation results.</p><p>In this work, we develop a new recommendation framework, i.e., Collaborator Recommendation Integrating Author’s Cooperation Strength and Research Interests (CRISI) on an attributed graph. It improves the quality of recommended node via double-weighting the structure and attributes as well as adopting the node replacement method. This can effectively recommend collaborators who have a close cooperative relationship with the recommended node. We conduct extensive experiments on two real-world datasets, and further analysis shows that the performance of our proposed CRISI model is superior to existing methods.</p></div>","PeriodicalId":72089,"journal":{"name":"Advances in computational intelligence","volume":"1 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s43674-021-00002-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50528121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Personalized recommendation: an enhanced hybrid collaborative filtering 个性化推荐：一种增强的混合协同过滤

Advances in computational intelligence Pub Date : 2021-05-22 DOI: 10.1007/s43674-021-00001-z

Parivash Pirasteh, Mohamed-Rafik Bouguelia, K. C. Santosh

引用次数: 8

Correction to: Advances in Computational Intelligence 更正:计算智能的进展

Advances in computational intelligence Pub Date : 2021-01-01 DOI: 10.1007/978-3-030-85099-9_36

I. Rojas, G. Joya, Andreu Català

引用次数: 0

Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part II 计算智能的进展:第16届国际人工神经网络工作会议，IWANN 2021，虚拟事件，2021年6月16-18日，会议录，第二部分

Advances in computational intelligence Pub Date : 2021-01-01 DOI: 10.1007/978-3-030-85099-9

引用次数: 0

Advances in Computational Intelligence: 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I 计算智能的进展:第16届国际人工神经网络工作会议，IWANN 2021，虚拟事件，2021年6月16-18日，会议录，第一部分

Advances in computational intelligence Pub Date : 2021-01-01 DOI: 10.1007/978-3-030-85030-2

引用次数: 0

Advances in Computational Intelligence: 20th Mexican International Conference on Artificial Intelligence, MICAI 2021, Mexico City, Mexico, October 25–30, 2021, Proceedings, Part I 计算智能进展:第20届墨西哥国际人工智能会议，MICAI 2021，墨西哥城，墨西哥，2021年10月25日至30日，会议录，第一部分

Advances in computational intelligence Pub Date : 2021-01-01 DOI: 10.1007/978-3-030-89817-5

引用次数: 2

Sparse Least Squares Support Vector Machines Based on Genetic Algorithms: A Feature Selection Approach 基于遗传算法的稀疏最小二乘支持向量机:一种特征选择方法

Advances in computational intelligence Pub Date : 2019-01-01 DOI: 10.1007/978-3-030-20518-8_42

Pedro Hericson Machado Araújo, A. R. Rocha Neto

引用次数: 1

A First Approximation to the Effects of Classical Time Series Preprocessing Methods on LSTM Accuracy 经典时间序列预处理方法对LSTM精度影响的初步逼近

Advances in computational intelligence Pub Date : 2019-01-01 DOI: 10.1007/978-3-030-20521-8_23

Daniel Trujillo Viedma, Antonio Jesús Rivera Rivas, Francisco Charte Ojeda, María José del Jesus Díaz

引用次数: 0

Modeling Detection of HIV in Cuba 古巴艾滋病病毒检测模型

Advances in computational intelligence Pub Date : 2011-06-08 DOI: 10.1007/978-3-642-21498-1_66

H. Arazoza, R. Lounes, A. S. Pérez, Jorge Barrios, Y. Hsieh

引用次数: 3

Advances in Computational Intelligence: 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, Mexico City, Mexico, October 12–17, 2020, Proceedings, Part II 计算智能进展:第19届墨西哥国际人工智能会议，MICAI 2020，墨西哥城，墨西哥，2020年10月12日至17日，会议录，第二部分

Advances in computational intelligence Pub Date : 1900-01-01 DOI: 10.1007/978-3-030-60887-3

Lourdes Martínez-Villaseñor, Oscar Herrera-Alcántara, Hiram Ponce, Félix A. Castro-Espinoza

引用次数: 2