复杂网络与数据挖掘:研究范式的比较和整合  

Comparative Study and Integration of Research Paradigms of Complex Networks and Data Mining

作　　者：沈斌[1] 

机构地区：[1]浙江大学宁波理工学院,浙江宁波315100

出　　处：《复杂系统与复杂性科学》2014年第1期48-52,59,共6页Complex Systems and Complexity Science

基　　金：国家自然科学基金(71271191);人社部留学人员科技活动项目择伏资助(2013年);浙江省自然科学基金(Y1110960)

摘　　要：在分析和对比复杂网络与数据挖掘两种范式的基础上,指出数据挖掘研究需要高度重视系统普适规律和内在机制的发现;复杂网络可以引入数据挖掘技术处理大数据,形成理论与数据的有机协同。进而探讨已有的复杂网络和数据挖掘交叉性探索工作,提出了范式整合的可能方向与途径。A Currently, the opportunity of integrating research paradigms of complex networks and data mining has come. On the basis of analyzing and comparing these two paradigms, it is pointed out that data mining research community should pay more attention to discovering universal laws and internal mechanisms of the system. For the research of complex networks, data mining tech- niques should be introduced to handle big data, and an integrated paradigm for the synergistic collaboration between theoretical model construction and data analytics should be ~ormed. Then, exploratory work of the integration of complex networks and data mining has been discussed, and the possible directions for paradigm integration also have been proposed.

关 键 词：信息挖掘 数据挖掘 研究范式 比较与整合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] N94[自动化与计算机技术—计算机科学与技术]