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 "hybrid noncoherent network coding"):
  Abstract: We describe a novel extension of subspace codes for noncoherent networks, suitable for use when the network is viewed as a communication system that introduces both dimension and symbol errors. We show that when symbol erasures occur in a significantly large number of different basis vectors transmitted through the network and when the min-cut of the networks is much smaller then the length of the transmitted codewords, the new family of codes outperforms their subspace code counterparts. #R##N#For the proposed coding scheme, termed hybrid network coding, we derive two upper bounds on the size of the codes. These bounds represent a variation of the Singleton and of the sphere-packing bound. We show that a simple concatenated scheme that represents a combination of subspace codes and Reed-Solomon codes is asymptotically optimal with respect to the Singleton bound. Finally, we describe two efficient decoding algorithms for concatenated subspace codes that in certain cases have smaller complexity than subspace decoders.

Includes members:
  Member "error resilience in distributed storage via rank metric codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "equivalence and characterizations of linear rank metric codes based on invariants")
  Member "new improvements on the echelon ferrers construction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "construction of subspace codes through linkage")
  Member "binary error correcting network codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "end to end error correcting codes on networks with worst case symbol errors")
  Member "recursive code construction for random networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new constructions of subspace codes using subsets of mrd codes in several blocks")
  Member "error correcting codes in projective spaces via rank metric codes and ferrers diagrams":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a note on echelon ferrers construction")
  Member "spread codes and spread decoding in network coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "symbol erasure correction capability of spread codes")
  Member "a rank metric approach to error control in random network coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "roos bound for skew cyclic codes in hamming and rank metric")
  Member "construction of large constant dimension codes with a prescribed minimum distance":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on some automorphisms of rational functions and their applications in rank metric codes")

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.IT(Information Theory)