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 "enumerative coding for grassmannian space"):
  Abstract: The Grassmannian space $\Gr$ is the set of all $k-$dimensional subspaces of the vector space~\smash{$\F_q^n$}. Recently, codes in the Grassmannian have found an application in network coding. The main goal of this paper is to present efficient enumerative encoding and decoding techniques for the Grassmannian. These coding techniques are based on two different orders for the Grassmannian induced by different representations of $k$-dimensional subspaces of $\F_q^n$. One enumerative coding method is based on a Ferrers diagram representation and on an order for $\Gr$ based on this representation. The complexity of this enumerative coding is $O(k^{5/2} (n-k)^{5/2})$ digit operations. Another order of the Grassmannian is based on a combination of an identifying vector and a reduced row echelon form representation of subspaces. The complexity of the enumerative coding, based on this order, is $O(nk(n-k)\log n\log\log n)$ digits operations. A combination of the two methods reduces the complexity on average by a constant factor.

Includes members:
  Member "large constant dimension codes and lexicodes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the lattice structure of linear subspace codes")
  Member "recursive code construction for random networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "new constructions of subspace codes using subsets of mrd codes in several blocks")
  Member "construction and covering properties of constant dimension codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a new construction for constant weight codes")
  Member "on metrics for error correction in network coding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "point line incidence on grassmannians and majority logic decoding of grassmann codes")
  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)