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: "extended alphabet finite context models"
  Abstract: Abstract   The normalized relative compression (NRC) is a recent dissimilarity measure, related to the Kolmogorov complexity. It has been successfully used in different applications, like DNA sequences, images or even ECG (electrocardiographic) signal. It uses a compressor that compresses a target string using exclusively the information contained in a reference string. One possible approach is to use finite-context models (FCMs) to represent the strings. A finite-context model calculates the probability distribution of the next symbol, given the previous k symbols. In this paper, we introduce a generalization of the FCMs, called extended-alphabet finite-context models (xaFCM), that calculates the probability of occurrence of the next d symbols, given the previous k symbols. We perform experiments on two different sample applications using the xaFCMs and the NRC measure: ECG biometric identification, using a publicly available database; estimation of the similarity between DNA sequences of two different, but related, species – chromosome by chromosome. In both applications, we compare the results against those obtained by the FCMs. The results show that the xaFCMs use less memory and computational time to achieve the same or, in some cases, even more accurate results.

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)