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: "index codes with minimum locality for three receiver unicast problems"
  Abstract: An index code for a broadcast channel with receiver side information is locally decodable if every receiver#R##N#can decode its demand using only a subset of the codeword#R##N#symbols transmitted by the sender instead of observing the entire#R##N#codeword. Local decodability in index coding improves the error#R##N#performance when used in wireless broadcast channels, reduces#R##N#the receiver complexity and improves privacy in index coding.#R##N#The locality of an index code is the ratio of the number of#R##N#codeword symbols used by each receiver to the number message#R##N#symbols demanded by the receiver. Prior work on locality in#R##N#index coding have considered only single unicast and singleuniprior problems, and the optimal trade-off between broadcast#R##N#rate and locality is known only for a few cases. In this paper we#R##N#identify the optimal broadcast rate (including among non-linear#R##N#codes) for all three receiver unicast problems when the locality#R##N#is equal to the minimum possible value, i.e., equal to one. The#R##N#index code that achieves this optimal rate is based on a clique#R##N#covering technique and is well known. The main contribution#R##N#of this paper is in providing tight converse results by relating#R##N#locality to broadcast rate, and showing that this known index#R##N#coding scheme is optimal when locality is equal to one. Towards#R##N#this we derive several structural properties of the side information#R##N#graphs of three receiver unicast problems, and combine them#R##N#with information theoretic arguments to arrive at a converse.

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)