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 "a novel measure of edge centrality in social networks"):
  Abstract: The problem of assigning centrality values to nodes and edges in graphs has been widely investigated during last years. Recently, a novel measure of node centrality has been proposed, called @k-path centrality index, which is based on the propagation of messages inside a network along paths consisting of at most @k edges. On the other hand, the importance of computing the centrality of edges has been put into evidence since 1970s by Anthonisse and, subsequently by Girvan and Newman. In this work we propose the generalization of the concept of @k-path centrality by defining the @k-path edge centrality, a measure of centrality introduced to compute the importance of edges. We provide an efficient algorithm, running in O(@km), being m the number of edges in the graph. Thus, our technique is feasible for large scale network analysis. Finally, the performance of our algorithm is analyzed, discussing the results obtained against large online social network datasets.

Includes members:
  Member "generalized louvain method for community detection in large networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressive sensing for cut improvement and local clustering")
  Member "grammar based geodesics in semantic networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the rdf virtual machine")
  Member "grammar based random walkers in semantic networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "active learning for graph embedding")

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)