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 "a characterization of a class of optimal three weight cyclic codes of dimension 3 over any finite field"):
  Abstract: It is well known that the problem of determining the weight distributions of families of cyclic codes is, in general, notoriously difficult. An even harder problem is to find characterizations of families of cyclic codes in terms of their weight distributions. On the other hand, it is also well known that cyclic codes with few weights have a great practical importance in coding theory and cryptography. In particular, cyclic codes having three nonzero weights have been studied by several authors, however, most of these efforts focused on cyclic codes over a prime field. In this work we present a characterization of a class of optimal three-weight cyclic codes of dimension 3 over any finite field. The codes under this characterization are, indeed, optimal in the sense that their lengths reach the Griesmer lower bound for linear codes. Consequently, these codes reach, simultaneously, the best possible coding capacity, and also the best possible capabilities of error detection and correction for linear codes. But because they are cyclic in nature, they also possess a rich algebraic structure that can be utilized in a variety of ways, particularly, in the design of very efficient coding and decoding algorithms. What is also worth pointing out, is the simplicity of the necessary and sufficient numerical conditions that characterize our class of optimal three-weight cyclic codes. As we already pointed out, it is a hard problem to find this kind of characterizations. However, for this particular case the fundamental tool that allowed us to find our characterization was the characterization for all two-weight irreducible cyclic codes that was introduced by B. Schmidt and C. White (2002). Lastly, another feature about the codes in this class, is that their duals seem to have always the same parameters as the best known linear codes.

Includes members:
  Member "several classes of cyclic codes with either optimal three weights or a few weights":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a class of functions with low valued walsh spectrum")
  Member "weight distributions of cyclic codes with respect to pairwise coprime order elements":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a class of functions with low valued walsh spectrum")
  Member "a class of three weight cyclic codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a class of narrow sense bch codes")
  Member "on the weight distributions of several classes of cyclic codes from apn monomials":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "several classes of cyclic codes with either optimal three weights or a few weights")
  Member "a characterization of two weight projective cyclic codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "several classes of cyclic codes with either optimal three weights or a few weights")

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)