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 "survey and taxonomy of lossless graph compression and space efficient graph representations"):
  Abstract: Various graphs such as web or social networks may contain up to trillions of edges. Compressing such datasets can accelerate graph processing by reducing the amount of I/O accesses and the pressure on the memory subsystem. Yet, selecting a proper compression method is challenging as there exist a plethora of techniques, algorithms, domains, and approaches in compressing graphs. To facilitate this, we present a survey and taxonomy on lossless graph compression that is the first, to the best of our knowledge, to exhaustively analyze this domain. Moreover, our survey does not only categorize existing schemes, but also explains key ideas, discusses formal underpinning in selected works, and describes the space of the existing compression schemes using three dimensions: areas of research (e.g., compressing web graphs), techniques (e.g., gap encoding), and features (e.g., whether or not a given scheme targets dynamic graphs). Our survey can be used as a guide to select the best lossless compression scheme in a given setting.

Includes members:
  Member "grammar based graph compression":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "constant delay traversal of grammar compressed graphs with bounded rank")
  Member "compressing networks with super nodes":
    also connected through other hyperedges:
      (none)
  Member "graphzip dictionary based compression for mining graph streams":
    also connected through other hyperedges:
      (none)
  Member "parallel construction of compact planar embeddings":
    also connected through other hyperedges:
      (none)
  Member "compressed representation of dynamic binary relations with applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "compressed data structures for binary relations in practice")
  Member "a succinct data structure for self indexing ternary relations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "extending general compact querieable representations to gis applications")
  Member "fully dynamic de bruijn graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "data structures to represent sets of k long dna sequences")
  Member "compressing graphs and indexes with recursive graph bisection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "techniques for inverted index compression")

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)