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 generalized core decomposition"):
  Abstract: The k-core of a graph is defined as the maximal subgraph in which every vertex is connected to at least k other vertices within that subgraph. In this work we introduce a distance-based generalization of the notion of k-core, which we refer to as the $(k,h)$-core, i.e., the maximal subgraph in which every vertex has at least k other vertices at distance $leq h$ within that subgraph. We study the properties of the $(k,h)$-core showing that it preserves many of the nice features of the classic core decomposition (e.g., its connection with the notion of distance-generalized chromatic number ) and it preserves its usefulness to speed-up or approximate distance-generalized notions of dense structures, such as h-club. Computing the distance-generalized core decomposition over large networks is intrinsically complex. However, by exploiting clever upper and lower bounds we can partition the computation in a set of totally independent subcomputations, opening the door to top-down exploration and to multithreading, and thus achieving an efficient algorithm.

Includes members:
  Member "mining maximal span cores from temporal networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a hybrid approach to temporal pattern matching")
  Member "when engagement meets similarity efficient k r core computation on social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey of community search over big graphs")
  Member "density friendly graph decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "computing the k densest subgraphs of a graph")
  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 "finding the hierarchy of dense subgraphs using nucleus decompositions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the power of pivoting for exact clique counting")
  Member "social resilience in online communities the autopsy of friendster":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "span core decomposition for temporal networks algorithms and applications")
  Member "fast exact shortest path distance queries on large networks by pruned landmark labeling":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "relaxing relationship queries on graph data")
  Member "truss decomposition in massive networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "efficient bitruss decomposition for large scale bipartite 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.DS(Data Structures and Algorithms)