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 "evaluating social networks using task focused network inference"):
  Abstract: Networks are representations of complex underlying social processes. However, the same given network may be more suitable to model one behavior of individuals than another. In many cases, aggregate population models may be more effective than modeling on the network. We present a general framework for evaluating the suitability of given networks for a set of predictive tasks of interest, compared against alternative, networks inferred from data. We present several interpretable network models and measures for our comparison. We apply this general framework to the case study on collective classification of music preferences in a newly available dataset of the this http URL social network.

Includes members:
  Member "network structure inference a survey motivations methods and applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "disentangling interpretable generative parameters of random and real world graphs")
  Member "inferring networks of substitutable and complementary products":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cube2net efficient query specific network construction with data cube organization")
  Member "multiplicative attribute graph model of real world networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graph generators state of the art and open challenges")
  Member "on the convexity of latent social network inference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep collaborative embedding for information cascade prediction")

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.SI(Social and Information Networks)