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 "overlapping community detection in networks based on link partitioning and partitioning around medoids"):
  Abstract: In this paper, we present a new method for detecting overlapping communities in networks with a predefined number of clusters. The overlapping communities in the graph are obtained by detecting the disjoint communities in the associated line graph by means of link partitioning and partitioning around medoids. Partitioning around medoids is done through the use of a distance function defined on the set of nodes of the linear graph. In the present paper, we consider the commute distance and amplified commute distance functions as distance functions. The performance of the proposed method is demonstrated by computational experiments on real-life instances.

Includes members:
  Member "modular networks for validating community detection algorithms":
    also connected through other hyperedges:
      (none)
  Member "metrics for community analysis a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "when less is more systematic analysis of cascade based community detection")
  Member "overlapping community detection in networks the state of the art and comparative study":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "meta learning with relational information for short sequences")
  Member "axioms for graph clustering quality functions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graph clustering via qubo and digital annealing")

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)