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: "detecting patterns can be hard circuit lower bounds for the string matching problem"
  Abstract: Detecting patterns in strings and images is a fundamental and well studied problem. We study the circuit complexity of the string matching problem under two popular choices of gates: De Morgan and threshold gates. For strings of length $n$ and patterns of length $\log n \ll k \leq n -o(n)$, we prove super polynomial lower bounds for De Morgan circuits of depth 2, and nearly linear lower bounds for depth 2 threshold circuits. For unbounded depth and $k \geq 2$, we prove a linear lower bound for (unbounded fan-in) De Morgan circuits. For certain values of $k$, we prove a $\Omega(\sqrt{n}/\log n)$ lower bound for general (no depth restriction) threshold circuits. Our proof for threshold circuits builds on a curious connection between detecting patterns and evaluating Boolean functions when the truth table of the function is given explicitly. Finally, we provide upper bounds on the size of circuits that solve the string matching problem.

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.CC(Computational Complexity)