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: "improved budgeted connected domination and budgeted edge vertex domination"
  Abstract: We consider the \emph{budgeted} version of the classical \emph{connected dominating set} problem (BCDS). Given a graph $G$ and an integer budget $k$, we seek to find a connected subset of at most $k$ vertices which maximizes the number of dominated vertices in $G$. We answer an open question in [Khuller, Purohit, and Sarpatwar,\ \emph{SODA 2014}] and thus we improve over the previous $(1-1/e)/13$ approximation. Our algorithm provides a $(1-1/e)/7$ approximation guarantee by employing an improved method for enforcing connectivity and performing tree decompositions. #R##N#We also consider the \emph{edge-vertex domination} variant, where an edge dominates its endpoints and all vertices neighboring them. In \emph{budgeted edge-vertex domination} (BEVD), we are given a graph $G$, and a budget $k$, and we seek to find a, not necessarily connected, subset of edges such that the number of dominated vertices in $G$ is maximized. We prove there exists a $(1-1/e)$-approximation algorithm. Also, for any $\epsilon > 0$, we present a $(1-1/e+\epsilon)$-inapproximability result by a gap-preserving reduction from the \emph{maximum coverage} problem. We notice that, in the connected case, BEVD becomes equivalent to BCDS. Moreover, we examine the ``dual'' \emph{partial edge-vertex domination} (PEVD) problem, where a graph $G$ and a quota $n'$ are given. The goal is to select a minimum-size set of edges to dominate at least $n'$ vertices in $G$. In this case, we present a $H(n')$-approximation algorithm by a reduction to the \emph{partial cover} 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.DS(Data Structures and Algorithms)