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 greedy heuristic for crossing angle maximization"
  Abstract: The crossing angle of a straight-line drawing $\Gamma$ of a graph $G=(V, E)$ is the smallest angle between two crossing edges in $\Gamma$. Deciding whether a graph $G$ has a straight-line drawing with a crossing angle of $90^\circ$ is $\mathcal NP$-hard. We propose a simple heuristic to compute a drawing with a large crossing angle. The heuristic greedily selects the best position for a single vertex in a random set of points. The algorithm is accompanied by a speed-up technique to compute the crossing angle of a straight-line drawing. We show the effectiveness of the heuristic in an extensive empirical evaluation. Our heuristic was clearly the winning algorithm (CoffeeVM) in the Graph Drawing Challenge 2017.

Connected through hyperedge HE-1 (induced by source paper "stress plus x spx graph layout"):
  with members:
    - "a heuristic approach towards drawings of graphs with high crossing resolution"
    - "an overview of gradient descent optimization algorithms"
    - "maximizing the total resolution of graphs"

Connected through hyperedge HE-2 (induced by source paper "geometric crossing minimization a scalable randomized approach"):
  with members:
    - "a heuristic approach towards drawings of graphs with high crossing resolution"
    - "drawing large graphs by multilevel maxent stress optimization"
    - "inserting multiple edges into a planar graph"

Connected through hyperedge HE-3 (induced by source paper "a survey on graph drawing beyond planarity"):
  with members:
    - "parameterized complexity of 1 planarity"
    - "minimum weight connectivity augmentation for planar straight line graphs"
    - "compact drawings of 1 planar graphs with right angle crossings and few bends"
    - "drawing subcubic 1 planar graphs with few bends few slopes and large angles"
    - "turning cliques into paths to achieve planarity"
    - "a heuristic approach towards drawings of graphs with high crossing resolution"
    - "on rac drawings of graphs with one bend per edge"
    - "recognizing optimal 1 planar graphs in linear time"

Connected through hyperedge HE-4 (induced by source paper "a heuristic approach towards drawings of graphs with high crossing resolution"):
  with members:
    - "a survey on graph drawing beyond planarity"
    - "geodesic obstacle representation of graphs"
    - "nic planar graphs"
    - "on the edge length ratio of outerplanar graphs"
    - "recognizing and drawing ic planar graphs"
    - "maximizing the total resolution of graphs"
    - "the straight line rac drawing problem is np hard"
    - "notes on large angle crossing graphs"

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)