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 "linear space approximate distance oracles for planar bounded genus and minor free graphs"):
  Abstract: A (1+e)-approximate distance oracle for a graph is a data structure that supports approximate point-to-point shortest-path-distance queries. The most relevant measures for a distance-oracle construction are: space, query time, and preprocessing time.#R##N##R##N#There are strong distance-oracle constructions known for planar graphs (Thorup, JACM'04) and, subsequently, minor-excluded graphs (Abraham and Gavoille, PODC'06). However, these require Ω(e-1n lg n) space for n-node graphs.#R##N##R##N#In this paper, for planar graphs, bounded-genus graphs, and minor-excluded graphs we give distance-oracle constructions that require only O(n) space. The big O hides only a fixed constant, independent of e and independent of genus or size of an excluded minor. The preprocessing times for our distance oracle are also faster than those for the previously known constructions. For planar graphs, the preprocessing time is O(nlg2 n). However, our constructions have slower query times. For planar graphs, the query time is O(e-2 lg2 n).#R##N##R##N#For all our linear-space results, we can in fact ensure, for any δ > 0, that the space required is only 1 + δ times the space required just to represent the graph itself.

Includes members:
  Member "improved distance queries in planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "almost optimal distance oracles for planar graphs")
  Member "exact distance oracles for planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a divide and conquer algorithm for two point l_1 shortest path queries in polygonal domains")
  Member "fast precise and dynamic distance queries":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on strong diameter padded decompositions")
  Member "shortest paths in planar graphs with real lengths in o n log 2n log log n time":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "level planar drawings with few slopes")
  Member "ramsey partitions and proximity data structures":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "labelings vs embeddings on distributed representations of distances")
  Member "fast construction of nets in low dimensional metrics and their applications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a data dependent algorithm for querying earth mover s distance with low doubling dimension")
  Member "maintaining information in fully dynamic trees with top trees":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "dynamic generators of topologically embedded graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "obtaining a canonical polygonal schema from a greedy homotopy basis with minimal mesh refinement")

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)