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: "the optimality of partial clique covering for index coding"
  Abstract: Partial clique covering is one of the most basic coding schemes for index coding problems, generalizing clique and cycle covering on the side information digraph and further reducing the achievable broadcast rate. In this paper, we start with partition multicast, a special case of partial clique covering with cover number 1, and show that partition multicast achieves the optimal broadcast rate of the multiple-unicast index coding if and only if the side information digraph is partially acyclic. A digraph is said to be partially acyclic if its sub-digraph induced by the vertex with maximum in-degree and its incoming neighbors in the complementary digraph is acyclic. We further extend to the general partial clique covering, offering sufficient conditions of its optimality and sub-optimality with the aid of strong connectivity decomposition. In addition, for some digraph classes, we also prove that the optimal broadcast rate can be approximated by partial clique covering (as well as by other basic schemes) within either a constant factor, or a multiplicative factor of $O(\frac{n}{\log n})$, or $O(n^\epsilon)$ for some $\epsilon \in (0,1)$.

Connected through hyperedge HE-1 (induced by source paper "linear programming approximations for index coding"):
  with members:
    - "approximate capacity of index coding for some classes of graphs"
    - "storage capacity of repairable networks"
    - "generalized interlinked cycle cover for index coding"
    - "a new index coding scheme exploiting interlinked cycles"
    - "graph theory versus minimum rank for index coding"
    - "local graph coloring and index coding"
    - "lexicographic products and the power of non linear network coding"
    - "linear index coding via semidefinite programming"

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)