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: "codes for erasures over directed graphs"
  Abstract: In this work we continue the study of a new class of codes, called \emph{codes over graphs}. Here we consider storage systems where the information is stored on the edges of a complete directed graph with $n$ nodes. The failure model we consider is of \emph{node failures} which are erasures of all edges, both incoming and outgoing, connected to the failed node. It is said that a code over graphs is a \textit{$\rho$-node-erasure-correcting code} if it can correct the failure of any $\rho$ nodes in the graphs of the code. While the construction of such optimal codes is an easy task if the field size is ${\cal O} (n^2)$, our main goal in the paper is the construction of codes over smaller fields. In particular, our main result is the construction of optimal binary codes over graphs which correct two node failures with a prime number of nodes.

Connected through hyperedge HE-1 (induced by source paper "private information retrieval in graph based replication systems"):
  with members:
    - "private information retrieval from mds coded data in distributed storage systems"
    - "private computation of systematically encoded data with colluding servers"
    - "codes for graph erasures"
    - "private information retrieval from storage constrained databases coded caching meets pir"
    - "multi message private information retrieval capacity results and near optimal schemes"
    - "pir array codes with optimal virtual server rate"
    - "multiround private information retrieval capacity and storage overhead"
    - "the capacity of robust private information retrieval with colluding databases"

Connected through hyperedge HE-2 (induced by source paper "double and triple node erasure correcting codes over graphs"):
  with members:
    - "codes for graph erasures"
    - "powers of tensors and fast matrix multiplication"
    - "zigzag codes mds array codes with optimal rebuilding"
    - "partial mds codes and their application to raid type of architectures"

Connected through hyperedge HE-3 (induced by source paper "codes for graph erasures"):
  with members:
    - "explicit constructions of high rate mds array codes with optimal repair bandwidth"
    - "explicit constructions of optimal access mds codes with nearly optimal sub packetization"
    - "repair optimal mds array codes over gf 2"
    - "zigzag codes mds array codes with optimal rebuilding"
    - "optimal exact regenerating codes for distributed storage at the msr and mbr points via a product matrix construction"

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)