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: "a new framework for strong connectivity and 2 connectivity in directed graphs"
  Abstract: In this paper, we investigate some basic problems related to the strong connectivity and to the $2$-connectivity of a directed graph, by considering the effect of edge and vertex deletions on its strongly connected components. Let $G$ be a directed graph with $m$ edges and $n$ vertices. We present a collection of $O(n)$-space data structures that, after $O(m+n)$-time preprocessing can accomplish the following tasks: $(i)$ Report in $O(n)$ worst-case time all the strongly connected components obtained after deleting a single edge (resp., a single vertex) in $G$. $(ii)$ Compute the total number of strongly connected components obtained after deleting a single edge (resp., vertex) in total worst-case $O(n)$ time for all edges (resp., for all vertices). $(iii)$ Compute the size of the largest and of the smallest strongly connected components obtained after deleting a single edge (resp., vertex) in total worst-case $O(n)$ time for all edges (resp., for all vertices). #R##N#All our bounds are tight. After the same $O(m+n)$-time preprocessing, we can also build an $O(n)$-space data structure that can answer in asymptotically optimal time the following basic $2$-edge and $2$-vertex connectivity queries on directed graphs: $(i)$ Test whether an edge or a vertex separates two query vertices in $O(1)$ worst-case time. $(ii)$ Report all edges or all vertices that separate two query vertices in optimal worst-case time. If there are $k>0$ separating edges (resp., separating vertices), then the time is $O(k)$ in the worst case. If there are no separating edges (resp., separating vertices), then the time is $O(1)$ in the worst case.

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.DS(Data Structures and Algorithms)