human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "a heuristic approach towards drawings of graphs with high crossing resolution"):
  Abstract: The crossing resolution of a non-planar drawing of a graph is the value of the minimum angle formed by any pair of crossing edges. Recent experiments have shown that the larger the crossing resolution is, the easier it is to read and interpret a drawing of a graph. However, maximizing the crossing resolution turns out to be an NP-hard problem in general and only heuristic algorithms are known that are mainly based on appropriately adjusting force-directed algorithms. #R##N#In this paper, we propose a new heuristic algorithm for the crossing resolution maximization problem and we experimentally compare it against the known approaches from the literature. Our experimental evaluation indicates that the new heuristic produces drawings with better crossing resolution, but this comes at the cost of slightly higher aspect ratio, especially when the input graph is large.

Includes members:
  Member "a survey on graph drawing beyond planarity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fan crossing free graphs")
  Member "geodesic obstacle representation of graphs":
    also connected through other hyperedges:
      (none)
  Member "a greedy heuristic for crossing angle maximization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stress plus x spx graph layout")
  Member "nic planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fan crossing free graphs")
  Member "on the edge length ratio of outerplanar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the edge length ratio of 2 trees")
  Member "recognizing and drawing ic planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fan crossing free graphs")
  Member "maximizing the total resolution of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "stress plus x spx graph layout")
  Member "the straight line rac drawing problem is np hard":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "rac drawings in subcubic area")

Question: Please tell me which class the source paper 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)