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: "structural properties of index coding capacity"
  Abstract: The index coding capacity is investigated through its structural properties. First, the capacity is characterized in three new multiletter expressions involving the clique number, Shannon capacity, and Lov\'asz theta function of the confusion graph, the latter notion introduced by Alon, Hassidim, Lubetzky, Stav, and Weinstein. The main idea is that every confusion graph can be decomposed into a small number of perfect graphs. The clique-number characterization is then utilized to show that the capacity is multiplicative under the lexicographic product of side information graphs, establishing the converse to an earlier result by Blasiak, Kleinberg, and Lubetzky. Second, sufficient and necessary conditions on the criticality of an index coding instance, namely, whether side information can be removed without reducing the capacity, are established based on the notion of unicycle, providing a partial answer to the question first raised by Tahmasbi, Shahrasbi, and Gohari. The necessary condition, along with other existing conditions, can be used to eliminate noncritical instances that do not need to be investigated. As an application of the established multiplicativity and criticality, only 10,634 (0.69%) out of 1,540,944 nonisomorphic six-message index coding instances are identified for further investigation, among which the capacity is still unknown for 119 instances.

Connected through hyperedge HE-1 (induced by source paper "on index coding for complementary graphs with focus on circular perfect graphs"):
  with members:
    - "duality codes and the integrality gap bound for index coding"
    - "index coding an interference alignment perspective"

Connected through hyperedge HE-2 (induced by source paper "groupcast index coding problem joint extensions"):
  with members:
    - "linear codes for broadcasting with noisy side information"
    - "optimal scalar linear codes for some classes of the two sender groupcast index coding problem"
    - "low complexity decoding for symmetric neighboring and consecutive side information index coding problems"
    - "index coding rank invariant extensions"
    - "the single uniprior index coding problem the single sender case and the multi sender extension"
    - "generalized lexicographic products and the index coding capacity"
    - "optimal vector linear index codes for some symmetric side information problems"
    - "a lifting construction for scalar linear index codes"

Connected through hyperedge HE-3 (induced by source paper "index coding rank invariant extensions"):
  with members:
    - "uniprior index coding"
    - "the single uniprior index coding problem the single sender case and the multi sender extension"
    - "structural properties of index coding capacity using fractional graph theory"
    - "optimal vector linear index codes for some symmetric side information problems"
    - "on a duality between recoverable distributed storage and index coding"
    - "topological interference management through index coding"
    - "on index coding and graph homomorphism"
    - "optimal index codes with near extreme rates"

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)