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 "codes in the space of multisets coding for permutation channels with impairments"):
  Abstract: Motivated by communication channels in which the transmitted sequences are subjected to random permutations, as well as by certain DNA storage systems, we study the error control problem in settings where the information is stored/transmitted in the form of multisets of symbols from a given finite alphabet. A general channel model is assumed in which the transmitted multisets are potentially impaired by insertions, deletions, substitutions, and erasures of symbols. Several constructions of error-correcting codes for this channel are described, and bounds on the size of optimal codes correcting any given number of errors are derived. The construction based on the notion of Sidon sets in finite Abelian groups is shown to be optimal, in the sense of the asymptotic scaling of code redundancy, for any error radius and alphabet size. It is also shown to be optimal in the stronger sense of maximal code cardinality in various cases.

Includes members:
  Member "fundamental limits of dna storage systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dna based storage models and fundamental limits")
  Member "duplication correcting codes for data storage in the dna of living organisms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal codes correcting a burst of deletions of variable length")
  Member "perfect codes in the discrete simplex":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on coding over sliced information")
  Member "compressing sets and multisets of sequences":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "loads of space local order agnosticism and bit flip efficient data structure codes")
  Member "multiset codes for permutation channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "perfect codes in the discrete simplex")
  Member "subset codes for packet networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "perfect codes in the discrete simplex")
  Member "codes in permutations and error correction for rank modulation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal constant weight codes under l_1 metric")

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)