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 "fast algorithms for intimate core group search in weighted graphs"):
  Abstract: Community search that finds query-dependent communities has been studied on various kinds of graphs. As one instance of community search, intimate-core group search over a weighted graph is to find a connected $k$-core containing all query nodes with the smallest group weight. However, existing state-of-the-art methods start from the maximal $k$-core to refine an answer, which is practically inefficient for large networks. In this paper, we develop an efficient framework, called local exploration k-core search (LEKS), to find intimate-core groups in graphs. We propose a small-weighted spanning tree to connect query nodes, and then expand the tree level by level to a connected $k$-core, which is finally refined as an intimate-core group. We also design a protection mechanism for critical nodes to avoid the collapsed $k$-core. Extensive experiments on real-life networks validate the effectiveness and efficiency of our methods.

Includes members:
  Member "k core minimization a game theoretic approach":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "manipulating node similarity measures in network")
  Member "a survey of community search over big graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "span core decomposition for temporal networks algorithms and applications")
  Member "an optimal and progressive approach to online search of top k influential communities":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey of community search over big graphs")
  Member "the minimum wiener connector problem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "span core decomposition for temporal networks algorithms and applications")
  Member "approximate closest community search in networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey of community search over big graphs")
  Member "truss decomposition in massive networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient bitruss decomposition for large scale bipartite graphs")
  Member "an o m algorithm for cores decomposition of networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fastgae fast scalable and effective graph autoencoders with stochastic subgraph decoding")

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)