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: "mass error correction codes for polymer based data storage"
  Abstract: We consider the problem of correcting mass readout errors in information encoded in binary polymer strings. Our work builds on results for string reconstruction problems using composition multisets [Acharya et al., 2015] and the unique string reconstruction framework proposed in [Pattabiraman et al., 2019]. Binary polymer-based data storage systems [Laure et al., 2016] operate by designing two molecules of significantly different masses to represent the symbols $\{{0,1\}}$ and perform readouts through noisy tandem mass spectrometry. Tandem mass spectrometers fragment the strings to be read into shorter substrings and only report their masses, often with errors due to imprecise ionization. Modeling the fragmentation process output in terms of composition multisets allows for designing asymptotically optimal codes capable of unique reconstruction and the correction of a single mass error [Pattabiraman et al., 2019] through the use of derivatives of Catalan paths. Nevertheless, no solutions for multiple-mass error-corrections are currently known. Our work addresses this issue by describing the first multiple-error correction codes that use the polynomial factorization approach for the Turnpike problem [Skiena et al., 1990] and the related factorization described in [Acharya et al., 2015]. Adding Reed-Solomon type coding redundancy into the corresponding polynomials allows for correcting $t$ mass errors in polynomial time using $t^2\, \log\,k$ redundant bits, where $k$ is the information string length. The redundancy can be improved to $\log\,k + t$. However, no decoding algorithm that runs polynomial-time in both $t$ and $n$ for this scheme are currently known, where $n$ is the length of the coded string.

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)