human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "the study about the analysis of responsiveness pair clustering to social network bipartite graph"):
  Abstract: In this study, regional (cities, towns and villages) data and tweet data are obtained from Twitter, and extract information of "purchase information (Where and what bought)" from the tweet data by morphological analysis and rule-based dependency analysis. Then, the "The regional information" and the "The information of purchase history (Where and what bought information)" are captured as bipartite graph, and Responsiveness Pair Clustering analysis (a clustering using correspondence analysis as similarity measure) is conducted. In this study, since it was found to be difficult to analyze a network such as bipartite graph having limitations in links by using modularity Q, responsiveness is used instead of modularity Q as similarity measure. As a result of this analysis, "regional information cluster" which refers to similar " The information of purchase history" nodes group is generated. Finally, similar regions are visualized by mapping the regional information cluster on the map. This visualization system is expected to contribute as an analytical tool for customers’ purchasing behaviour and so on.

Includes members:
  Member "a simplified approach for quality management in data warehouse":
    also connected through other hyperedges:
      (none)
  Member "gv index scientific contribution rating index that takes into account the growth degree of research area and variance values of the publication year of cited paper":
    also connected through other hyperedges:
      (none)
  Member "a simplified approach for quality management in data warehouse":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CY(Computers and Society)