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: "indexing point sets for approximate bottleneck distance queries"
  Abstract: The {\em bottleneck distance} is a natural measure of the distance between two finite point sets of equal cardinality. In this work, we consider the problem of indexing a set of $m$ planar point sets (of varying sizes) to create a database $D$ that supports nearest bottleneck distance queries: given a query point set $Q$ of size $n$, the point sets $P \in D$ that are closest in terms of bottleneck distance are returned. Without loss of generality, we assume that all point sets belong to the unit box $[0,1]^2$ in the plane. The main contribution of this work is a {\em trie}-based data structure that is space efficient and supports $8$-approximate nearest bottleneck queries in $O(-\lg(d_B(D,Q)) \min(m,{10}^n) n \lg^3 n)$ time, where $d_B(D,Q)$ is the minimum bottleneck distance from $Q$ to any point set in $D$. A direct consequence, of independent interest, is a simple $O(-\lg(d_B(P,Q)) n \lg^3 n)$ time algorithm to $2 \sqrt{2}$-approximate $d_B(P,Q)$, for any two point sets $P$ and $Q$. Finally, the querying algorithm proposed is easily adapted to support nearest subset and superset queries.

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.CG(Computational Geometry)