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 "the densest k subhypergraph problem"):
  Abstract: The Densest k-Subgraph (DkS) problem, and its corresponding minimization problem Smallest p-Edge Subgraph (SpES), have come to play a central role in approximation algorithms. This is due both to their practical importance, and their usefulness as a tool for solving and establishing approximation bounds for other problems. These two problems are not well understood, and it is widely believed that they do not an admit a subpolynomial approximation ratio (although the best known hardness results do not rule this out). In this paper we generalize both DkS and SpES from graphs to hypergraphs. We consider the Densest k-Subhypergraph problem (given a hypergraph (V,E), find a subset W ⊆ V of k vertices so as to maximize the number of hyperedges contained in W ) and define the Minimum p-Union problem (given a hypergraph, choose p of the hyperedges so as to minimize the number of vertices in their union). We focus in particular on the case where all hyperedges have size 3, as this is the simplest non-graph setting. For this case we provide an O(n4(4− √ 3)/13+ ) ≤ O(n )-approximation (for arbitrary constant > 0) for Densest k-Subhypergraph and an O(n)-approximation for Minimum p-Union. We also give an O( √ m)-approximation for Minimum p-Union in general hypergraphs. Finally, we examine the interesting special case of interval hypergraphs (instances where the vertices are a subset of the natural numbers and the hyperedges are intervals of the line) and prove that both problems admit an exact polynomial time solution on these instances. ∗Department of Computer Science, Ben Gurion University. Partially supported by ISF grant 1002/14. Email: chlamtac@cs.bgu.ac.il. †Department of Computer Science, Johns Hopkins University. Partially supported by NSF grants 1464239 and 1535887. Email: mdinitz@cs.jhu.edu ‡ICE-TCS, School of Computer Science, Reykjavik University. Supported by Icelandic Research Fund grants 120032011 and 152679-051. Email: christiank@ru.is. §Computer Science Department, Rutgers University, Camden, NY, USA. Partially supported by NSF grants 1218620 and 1540547. Email: guyk@crab.rutgers.edu ¶Department of Computer Science, The Graduate Center, CUNY, USA. Email: grabanca@gmail.com ar X iv :1 60 5. 04 28 4v 1 [ cs .D S] 1 3 M ay 2 01 6

Includes members:
  Member "approximation algorithms for hypergraph small set expansion and small set vertex expansion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "planted models for k way edge and vertex expansion")
  Member "the complexity of approximating vertex expansion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "planted models for k way edge and vertex expansion")
  Member "approximating semi matchings in streaming and in two party communication":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "metric sublinear algorithms via linear sampling")
  Member "everywhere sparse spanners via dense subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "lasserre integrality gaps for graph spanners and related problems")
  Member "approximation algorithms and hardness of the k route cut problem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "downgrading to minimize connectivity")
  Member "small approximate pareto sets for bi objective shortest paths and other problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "quasi polynomial algorithms for list coloring of nearly intersecting hypergraphs")
  Member "dial a ride from k forest":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reachability preservers new extremal bounds and approximation algorithms")

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)