human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "evolution of communities with focus on stability"
  Abstract: Community detection is an important tool for analyzing the social graph of mobile phone users. The problem of nding communities in static graphs has been widely studied. However, since mobile social networks evolve over time, static graph algorithms are not sucient. To be useful in practice (e.g. when used by a telecom analyst), the stability of the partitions becomes critical. We tackle this particular use case in this paper: tracking evolution of com- munities in dynamic scenarios with focus on stability. We propose two modications to a widely used static community detection algorithm: we introduce xed nodes and preferential attachment to pre-existing com- munities. We then describe experiments to study the stability and quality of the resulting partitions on real-world social networks, represented by monthly call graphs for millions of subscribers.

Connected through hyperedge HE-1 (induced by source paper "snel sql native execution for llvm"):
  with members:
    - "the value of big data for credit scoring enhancing financial inclusion using mobile phone data and social network analytics"
    - "uncovering the spread of chagas disease in argentina and mexico"
    - "comparison of feature extraction methods and predictors for income inference"
    - "inference of users demographic attributes based on homophily in communication networks"
    - "social events in a time varying mobile phone graph"
    - "social network analytics for churn prediction in telco"
    - "the city pulse of buenos aires"
    - "prepaid or postpaid that is the question novel methods of subscription type prediction in mobile phone services"

Question: Please tell me which class the center node 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.SI(Social and Information Networks)