human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "fractional repetition and erasure batch codes"
  Abstract: Batch codes are a family of codes that represent a distributed storage system (DSS) of $n$ nodes so that any batch of $t$ data symbols can be retrieved by reading at most one symbol from each node. Fractional repetition codes are a family of codes for DSS that enable efficient uncoded repairs of failed nodes. In this work these two families of codes are combined to obtain fractional repetition batch (FRB) codes which provide both uncoded repairs and parallel reads of subsets of stored symbols. In addition, new batch codes which can tolerate node failures are considered. This new family of batch codes is called erasure combinatorial batch codes (ECBCs). Some properties of FRB codes and ECBCs and examples of their constructions based on transversal designs and affine planes are presented.

Connected through hyperedge HE-1 (induced by source paper "functional repair codes a view from projective geometry"):
  with members:
    - "cooperative repair constructions of optimal mds codes for all admissible parameters"
    - "on the achievability region of regenerating codes for multiple erasures"
    - "a class of msr codes for clustered distributed storage"
    - "increasing availability in distributed storage systems via clustering"
    - "locality and availability of array codes constructed from subspaces"
    - "a tight lower bound on the sub packetization level of optimal access msr and mds codes"
    - "optimal fractional repetition codes and fractional repetition batch codes"
    - "on the combinatorics of locally repairable codes via matroid theory"

Connected through hyperedge HE-2 (induced by source paper "load balanced fractional repetition codes"):
  with members:
    - "nearly optimal constructions of pir and batch codes"
    - "irregular fractional repetition code optimization for heterogeneous cloud storage"
    - "optimal fractional repetition codes based on graphs and designs"
    - "codes with locality for two erasures"
    - "batch codes through dense graphs without short cycles"
    - "fractional repetition codes with flexible repair from combinatorial designs"
    - "distributed storage codes with repair by transfer and nonachievability of interior points on the storage bandwidth tradeoff"
    - "cooperative regenerating codes"

Connected through hyperedge HE-3 (induced by source paper "multiset combinatorial batch codes"):
  with members:
    - "bounds and constructions of codes with multiple localities"
    - "locality and availability in distributed storage"
    - "optimal combinatorial batch codes based on block designs"
    - "on an extremal hypergraph problem related to combinatorial batch codes"
    - "combinatorial batch codes a lower bound and optimal constructions"

Connected through hyperedge HE-4 (induced by source paper "optimal fractional repetition codes based on graphs and designs"):
  with members:
    - "fractional repetition codes with flexible repair from combinatorial designs"
    - "optimal combinatorial batch codes based on block designs"
    - "zigzag codes mds array codes with optimal rebuilding"
    - "reconstruction and repair degree of fractional repetition codes"
    - "replication based storage systems with local repair"
    - "locally repairable codes with multiple repair alternatives"
    - "exact repair regenerating codes via layered erasure correction and block designs"
    - "enumerating some fractional repetition codes"

Question: Please tell me which class the center node 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)