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: "on multi source networks enumeration rate region computation and hierarchy"
  Abstract: This paper investigates the enumeration, rate region computation, and hierarchy of general multi-source multi-sink hyperedge networks under network coding, which includes multiple network models, such as independent distributed storage systems and index coding problems, as special cases. A notion of minimal networks and a notion of network equivalence under group action are defined. An efficient algorithm capable of directly listing single minimal canonical representatives from each network equivalence class is presented and utilized to list all minimal canonical networks with up to 5 sources and hyperedges. Computational tools are then applied to obtain the rate regions of all of these canonical networks, providing exact expressions for 744,119 newly solved network coding rate regions corresponding to more than 2 trillion isomorphic network coding problems. In order to better understand and analyze the huge repository of rate regions through hierarchy, several embedding and combination operations are defined so that the rate region of the network after operation can be derived from the rate regions of networks involved in the operation. The embedding operations enable the definition and determination of a list of forbidden network minors for the sufficiency of classes of linear codes. The combination operations enable the rate regions of some larger networks to be obtained as the combination of the rate regions of smaller networks. The integration of both the combinations and embedding operators is then shown to enable the calculation of rate regions for many networks not reachable via combination operations alone.

Connected through hyperedge HE-1 (induced by source paper "constrained linear representability of polymatroids and algorithms for computing achievability proofs in network coding"):
  with members:
    - "mapping the region of entropic vectors with support enumeration information geometry"
    - "characterizing the rate region of the 4 3 3 exact repair regenerating codes"
    - "linear network coding linear index coding and representable discrete polymatroids"
    - "path gain algebraic formulation for the scalar linear network coding problem"
    - "a projection method for derivation of non shannon type information inequalities"

Connected through hyperedge HE-2 (induced by source paper "optimization based linear network coding for general connections of continuous flows"):
  with members:
    - "a linear network code construction for general integer connections based on the constraint satisfaction problem"
    - "the two unicast problem"
    - "decentralized constraint satisfaction"
    - "index coding an interference alignment perspective"
    - "scalar linear solvability of matroidal networks associated with representable matroids"
    - "optimal reverse carpooling over wireless networks a distributed optimization approach"
    - "on the index coding problem and its relation to network coding and matroid theory"
    - "minimum cost multicast over coded packet networks"

Connected through hyperedge HE-3 (induced by source paper "a linear network code construction for general integer connections based on the constraint satisfaction problem"):
  with members:
    - "the two unicast problem"
    - "precoding based network alignment for three unicast sessions"
    - "achievable rate regions for network coding"
    - "index coding an interference alignment perspective"
    - "computing bounds on network capacity regions as a polytope reconstruction problem"
    - "scalar linear solvability of matroidal networks associated with representable matroids"
    - "on the index coding problem and its relation to network coding and matroid theory"

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)