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: "a projection method for derivation of non shannon type information inequalities"
  Abstract: In 1998, Zhang and Yeung found the first unconditional non-Shannon-type information inequality. Recently, Dougherty, Freiling and Zeger gave six new unconditional non-Shannon-type information inequalities. This work generalizes their work and provides a method to systematically derive non-Shannon-type information inequalities. An application of this method reveals new 4-variable non-Shannon-type information inequalities.

Connected through hyperedge HE-1 (induced by source paper "partition symmetrical entropy functions"):
  with members:
    - "conditional information inequalities for entropic and almost entropic points"
    - "on the non robustness of essentially conditional information inequalities"
    - "entropy functions and determinant inequalities"
    - "on essentially conditional information inequalities"
    - "non shannon information inequalities in four random variables"
    - "average entropy functions"
    - "information rates of minimal non matroid related access structures"
    - "dualities between entropy functions and network codes"

Connected through hyperedge HE-2 (induced by source paper "constrained linear representability of polymatroids and algorithms for computing achievability proofs in network coding"):
  with members:
    - "on multi source networks enumeration rate region computation and hierarchy"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "explicit polyhedral bounds on network coding rate regions via entropy function region algorithms symmetry and computation"):
  with members:
    - "guessing numbers of odd cycles"
    - "characterizing the rate region of the 4 3 3 exact repair regenerating codes"
    - "achievable rate regions for network coding"
    - "non shannon information inequalities in four random variables"

Connected through hyperedge HE-4 (induced by source paper "mapping the region of entropic vectors with support enumeration information geometry"):
  with members:
    - "entropy region and convolution"
    - "equivalence of two proof techniques for non shannon type inequalities"
    - "finite p groups entropy vectors and the ingleton inequality for nilpotent groups"
    - "non shannon information inequalities in four random variables"
    - "linear rank inequalities on five or more variables"
    - "mission impossible computing the network coding capacity region"
    - "entropy vectors and network codes"
    - "dualities between entropy functions and network codes"

Connected through hyperedge HE-5 (induced by source paper "characteristic dependent linear rank inequalities with applications to network coding"):
  with members:
    - "achievable rate regions for network coding"
    - "lexicographic products and the power of non linear network coding"
    - "linear rank inequalities on five or more variables"
    - "entropy vectors and network codes"

Connected through hyperedge HE-6 (induced by source paper "equivalence of two proof techniques for non shannon type inequalities"):
  with members:
    - "on essentially conditional information inequalities"

Connected through hyperedge HE-7 (induced by source paper "on essentially conditional information inequalities"):
  with members:
    - "dualities between entropy functions and network codes"

Connected through hyperedge HE-8 (induced by source paper "non shannon information inequalities in four random variables"):
  with members:
    - "entropy vectors and network 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)