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 "distance labelings on random power law graphs"):
  Abstract: A {\it Distance Labeling} scheme is a data structure that can answer shortest path queries on a graph. Experiment results from several recent studies (Akiba et al.'13, Delling et al.'14) found very efficient and very accurate labeling schemes, which scale to social and information networks with tens of millions of vertices and edges. Such a finding is not expected in the worst case, since even for graphs with maximum degree $3$, it is known that any distance labeling requires $\Omega{(n^{3/2})}$ space (Gavoille et al.'03). On the other hand, social and information networks have a heavy-tailed degree distribution and small average distance, which are not captured in the worst case. #R##N#In this paper, we fill in the gap between empirical and worst case results. We consider distance labeling schemes on random graph models with a power law degree distribution. For such graphs, we show that simple breadth-first-search based algorithm can find near optimal labeling schemes. The intuition behind our proof reveals that the distances between different pairs of vertices are almost independent, even for polynomially many pairs.

Includes members:
  Member "an axiomatic and an average case analysis of algorithms and heuristics for metric properties of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parameterized complexity of diameter")
  Member "algorithmic and hardness results for the hub labeling problem":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exploiting hopsets improved distance oracles for graphs of constant highway dimension and beyond")
  Member "on the complexity of hub labeling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "pruning based distance sketches with provable guarantees on random graphs")
  Member "fast exact shortest path distance queries on large networks by pruned landmark labeling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "relaxing relationship queries on graph data")
  Member "approximate distance oracles with improved preprocessing time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "faster approximation algorithms for computing shortest cycles on weighted graphs")
  Member "linear space approximate distance oracles for planar bounded genus and minor free graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "holiest minimum cost paths and flows in surface graphs")

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)