AceMap学术地图与AceKG学术知识图谱——学术数据可视化
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摘要
学术大数据能为科研人员提供信息上的帮助.针对传统学术搜索引擎只提供搜索结果而不进行分析的情况,基于AceMap提出的学术地图的概念,设计了多种类型的学术地图,将学术信息可视化地展现给用户.针对SQL数据库多表联合查询的形式不利于生成用户定制的学术地图的问题,提出将其以三元组的形式储存为知识图谱AceKG.该方法有助于用户定制地图、异构地图绘制功能的实现,并且能通过嵌入算法为各种类型的实体生成相关性地图.通过对学术数据的可视化展示,能使用户更直观地了解到感兴趣的学术内容,提高了学术平台的实用性.
Academic big data can provide help on information to researchers.While traditional academic search engines only offer search results without analysis,academic map is proposed based on AceMap,visualizing academic information to users in form of graph with various types of designed maps.When SQL-based database is not capable for generating customized academic map,AceKG is proposed to store data in form of triplets.AceKG can help realize the heterogeneous and customized map generator and can generate correlation map for any type of entity after embedding.Through the visualization of academic data,users are able to find points of interest more intuitively,thus improves the practicality of academic platform.
Academic big data can provide help on information to researchers.While traditional academic search engines only offer search results without analysis,academic map is proposed based on AceMap,visualizing academic information to users in form of graph with various types of designed maps.When SQL-based database is not capable for generating customized academic map,AceKG is proposed to store data in form of triplets.AceKG can help realize the heterogeneous and customized map generator and can generate correlation map for any type of entity after embedding.Through the visualization of academic data,users are able to find points of interest more intuitively,thus improves the practicality of academic platform.
引文
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[7] JOLLIFFE I T.Principal component analysis[M].Berlin:Springer,1986:115-128.
[2] HU Y.Efficient,high-quality force-directed graph drawing[J].Mathematica Journal,1984,10(1):37-71.
[3] JACOMY M,BASTIAN M,HEYMANN S.Gephi:An open source software for exploring and manipulating networks[C]∥International AAAI Conference on Weblogs and Social Media.San Jose:3rd International AAAI Conference on Weblogs and Social Media,2009.
[4] JACOMY M,VENTURINI T,HEYMANN S,et al.ForceAtlas2,a continuous graph layout algorithm for handy network visualization designed for the gephi software[J].Plos One,2014,9(6):e98679.
[5] BLONDEL V D,GUILLAUME J L,LAMBIOTTE R,et al.Fast unfolding of communities in large networks[J].Journal of Statistical Mechanics,2008,2008(10):155-168.
[6] YANG B,YIH W T,HE X,et al.Embedding entities and relations for learning and inference in knowledge bases[C]∥International Conference on Learning Representations.San Diego:3rd International Conference on Learning Representations,2015.
[7] JOLLIFFE I T.Principal component analysis[M].Berlin:Springer,1986:115-128.