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 the number of optimal index codes"
  Abstract: In Index coding there is a single sender with multiple messages and multiple receivers each wanting a different set of messages and knowing a different set of messages a priori. The Index Coding problem is to identify the minimum number of transmissions (optimal length) to be made so that all receivers can decode their wanted messages using the transmitted symbols and their respective prior information and also the codes with optimal length. Recently it was shown that different optimal length codes perform differently in a wireless channel. Towards identifying the best optimal length index code one needs to know the number of optimal length index codes. In this paper we present results on the number of optimal length index codes making use of the representation of an index coding problem by an equivalent network code. We give the minimum number of codes possible with the optimal length. This is done using a simpler algebraic formulation of the problem compared to the approach of Koetter and Medard.

Connected through hyperedge HE-1 (induced by source paper "unicast uniprior index coding problems minrank and criticality"):
  with members:
    - "on critical index coding problems"
    - "topological interference management through index coding"
    - "critical graphs in index coding"
    - "index coding an interference alignment perspective"
    - "optimal index codes for a class of multicast networks with receiver side information"
    - "on the index coding problem and its relation to network coding and matroid theory"

Connected through hyperedge HE-2 (induced by source paper "maximum likelihood decoder for index coded psk modulation for priority ordered receivers"):
  with members:
    - "index codes for the gaussian broadcast channel using quadrature amplitude modulation"
    - "index coded psk modulation"
    - "on the number of optimal linear index codes for unicast index coding problems"
    - "optimal index codes for a class of multicast networks with receiver side information"

Connected through hyperedge HE-3 (induced by source paper "optimal scalar linear index codes for one sided neighboring side information problems"):
  with members:
    - "noisy index coding with psk and qam"
    - "optimal scalar linear index codes for some symmetric multiple unicast problems"
    - "index coding an interference alignment perspective"
    - "optimal index codes for a class of multicast networks with receiver side information"

Connected through hyperedge HE-4 (induced by source paper "on the number of optimal linear index codes for unicast index coding problems"):
  with members:
    - "optimal index coding with min max probability of error over fading channels"
    - "optimal index codes for a class of multicast networks with receiver side information"
    - "dynamic index coding for wireless broadcast networks"
    - "error correction for index coding with side information"
    - "on the index coding problem and its relation to network coding and matroid theory"
    - "non linear index coding outperforming the linear optimum"

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)