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 "streaming verification of graph properties"):
  Abstract: Streaming interactive proofs (SIPs) are a framework for outsourced computation, so that a computationally limited streaming client (the verifier) hands over a large data set to an untrusted server (the prover) in the cloud and the two parties run a protocol to confirm the correctness of result with high probability. #R##N#SIPs are particularly interesting for problems that are hard to solve (or even approximate) well in a streaming setting. The most notable of these problems is finding maximum matchings, which has received intense interest in recent years but has strong lower bounds even for constant factor approximations. In this paper, we present efficient streaming interactive proofs that can verify maximum matchings exactly. Our results cover all flavors of matchings (bipartite/non-bipartite and weighted). In addition, we also present streaming verifiers for approximate metric TSP. In particular, these are the first efficient results for weighted matchings and for metric TSP in any streaming verification model. #R##N#Our streaming verifiers use only polylogarithmic space while exchanging only polylogarithmic communication with the prover in addition to the output size of the relevant solution and its certificate size. Our protocols use $\log n$ rounds of communication, but can be modified to work in constant rounds with a slight increase in total communication cost in some cases. #R##N#Our protocols work by constructing a linear map from the edge updates to updates of a specially constructed higher dimensional tensor. We then formulate the graph-theoretic construct as a series of inverse frequency distribution questions on this tensor, and verify the answers using fingerprinting and low-degree polynomial extensions.

Includes members:
  Member "bipartite perfect matching is in quasi nc":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "from independent sets and vertex colorings to isotropic spaces and isotropic decompositions")
  Member "rational proofs with multiple provers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "non cooperative rational interactive proofs")
  Member "tight bounds for linear sketches of approximate matchings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the sketching complexity of graph and hypergraph counting")
  Member "sublinear estimation of weighted matchings in dynamic data streams":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "space efficient approximation to maximum matching size from uniform edge samples")
  Member "maximum matching in turnstile streams":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "two player hidden pointer chasing and multi pass lower bounds in turnstile streams")
  Member "sketching cuts in graphs and hypergraphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism")
  Member "an improved interactive streaming algorithm for the distinct elements problem":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "streaming verification in data analysis")
  Member "semi streaming algorithms for annotated graph streams":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "approximate mathbb f _2 sketching of valuation functions")

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)