“智慧校园”学者画像系统研究
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摘要
随着大数据时代的到来,学术相关数据呈指数增长趋势。同时,用来刻画用户行为的用户画像,近期在各个领域得到了广泛应用。通过分析挖掘与学者相关的学术数据,可以对学者进行全方位、高精度的画像构建,这对研究学者的学术行为有重要的作用。本文介绍了"智慧校园"学者画像系统及系统的相关技术点与功能特色,并将其与其他主流学者画像系统进行对比分析。结果显示,该系统在研究学者的学术谱系、研究脉络等方面存在一定的优势与特色。
With the arrival of the era of big data, the academic data shows an exponential growth trend. At the same time, as a modeling method of user, user profile has been widely used in various fields recently. By analyzing and mining academic data related to scholars, we can construct a full-scale and accurate profile for scholar, which plays an important role in researching scholars' academic behavior. This paper introduces not only the scholar profile system smart campus, but also its key methods and functional features. And we compare it with other mainstream scholar profile systems. The result shows that the system has certain advantages and characteristics such as the scholars' academic pedigree and relative research.
With the arrival of the era of big data, the academic data shows an exponential growth trend. At the same time, as a modeling method of user, user profile has been widely used in various fields recently. By analyzing and mining academic data related to scholars, we can construct a full-scale and accurate profile for scholar, which plays an important role in researching scholars' academic behavior. This paper introduces not only the scholar profile system smart campus, but also its key methods and functional features. And we compare it with other mainstream scholar profile systems. The result shows that the system has certain advantages and characteristics such as the scholars' academic pedigree and relative research.
引文
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[23]常欢,吕瑞花,张佳静.学术谱系内合作网络研究--以刘东生为核心的第四纪学术谱系为例[J].情报理论与实践,2016,39(4):14-19.
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[27]SINHA A,SHEN Z,SONG Y,et al.An Overview of Microsoft Academic Service(MAS)and Applications[C]//Proceedings of the 24th International Conference on World Wide Web.Florence:ACM,2015.
[2]ANNEWIL H,SATU A.Google Scholar,Scopus and the Web of Science:A Longitudinal and Cross-Disciplinary Comparison[M].New York:Springer-Verlag New York,2016.
[3]魏瑞斌,郭一娴.基于用户体验的百度学术应用研究[J].现代情报,2017(5):91-99.
[4]TANG J,ZHANG J,YAO L,et al.Arnetminer:Extraction and Mining of Academic Social Networks[C]//Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.Las Vegas:ACM,2008.
[5]ZHOU P,SHI W,TIAN J,et al.Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics.Berlin:ACM,2016.
[6]LIN Y,SHEN S,LIU Z,et al.Neural relation extraction with selective attention over instances[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics.Berlin:ACM,2016.
[7]YANG D,WANG S,LI Z.Ensemble neural relation extraction with adaptive boosting[C]//Proceedings of the TwentySeventh International Joint Conference on Artificial Intelligence.Stockholm:ACM,2018.
[8]YOSHIDA M,IKEDA M,ONO S,et al.Person name disambiguation by bootstrapping[C]//Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval.Geneva:ACM,2010.
[9]LOUPPE G,AI-NATSHEH H,SUSIK M,et al.Ethnicity sensitive author disambiguation using semi-supervised learning[C]//International Conference on Knowledge Engineering and the Semantic Web.Prague:Springer,2016.
[10]ZHANG Y,ZHANG F,YAO P,et al.Name Disambiguation in AMiner:Clustering,Maintenance,and Human in the Loop[C]//Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery&Data Mining,London:ACM,2018.
[11]FAN X M,WANG J Y,LV B,et al.GHOST:an effective graph-based framework for name distinction[C]//Proceedings of the 17th ACM Conference on Information and Knowledge Management.Napa Valley:ACM,2008.
[12]TANG J,FONG A C M,WANG B,et al.A unified probabilistic framework for name disambiguation in digital library[J].IEEE Transactions on Knowledge&Data Engineering,2012,24(6):975-987.
[13]ZHANG B C,HASAN M.Name Disambiguation in Anonymized Graphs using Network Embedding[C]//Proceedings of the 2017ACM on Conference on Information and Knowledge Management.Singapore:ACM,2017.
[14]YIN H,BENSON A R,LESKOVEC J,et al.Local higherorder graph clustering[C]//Proceedings of the 23rd ACMSIGKDD International Conference on Knowledge Discovery and Data Mining.Halifax:ACM,2017.
[15]EPASTO A,LATTANZI S,LEME R P.Ego-Splitting Framework:From Non-Overlapping to Overlapping Clusters[C]//Proceedings of the 23rd ACM SIGK DD Inter national Conference on Knowledge Discovery and Data Mining.Halifax:ACM,2017.
[16]FOLINO F,PIZZUTI C.An evolutionary multiobjective approach for community discovery in dynamic networks[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(8):1838-1852.
[17]MA X,DONG D.Evolutionar y nonnegative matrix factorization algorithms for community detection in dynamic networks[J].IEEE Transactions on Knowledge and Data Engineering,2017,29(5):1045-1058.
[18]NIU X,SI W,WU C Q.A label-based evolutionary computing approach to dynamic community detection[J].Computer Communications,2017,108(8):110-122.
[19]WU B,ZHANG C,GUO Q.A Parallel Network Community Detection Algorithm Based on Distance Dynamics[C]//Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.Sydney:ACM,2017.
[20]ZHANG C,ZHANG Y,WU B.A Parallel Community Detection Algorithm Based on Incremental Clustering in D y na m ic Net work[C]//2018 I EEE/ACM I nt er nat ional Conference on Advances in Social Networks Analysis and Mining.Barcelona:IEEE,2018.
[21]尹友明.Java语言与Java技术概述[J].中国新技术新产品,2011(6):99.
[22]李盛庆,蔡国永.复杂网络领域科研合著网络演化及知识传播特点研究[J].现代图书情报技术,2013(5):64-72.
[23]常欢,吕瑞花,张佳静.学术谱系内合作网络研究--以刘东生为核心的第四纪学术谱系为例[J].情报理论与实践,2016,39(4):14-19.
[24]胡化凯,丁兆君,陈崇斌,等.当代中国物理学家学术谱系[M].上海:上海交通大学出版社,2016:3.
[25]WANG W,LIU J Y,XIA F,et al.Shifu:Deep Learning Based Advisor-Advisee Relationship Mining in Scholarly Big Data[C]//Proceedings of the 26th International Conference on World Wide Web Companion.Perth:2017.
[26]BLONDE V D,GUILLAUME J L,LAMBIOTTE R,et al.Fast unfolding of communities in large networks[J].Journal of Statistical Mechanics:Theory and Experiment,2008(10):P10008.
[27]SINHA A,SHEN Z,SONG Y,et al.An Overview of Microsoft Academic Service(MAS)and Applications[C]//Proceedings of the 24th International Conference on World Wide Web.Florence:ACM,2015.