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 "on compressing permutations and adaptive sorting"):
  Abstract: Previous compact representations of permutations have focused on adding a small index on top of the plain data $ $, in order to efficiently support the application of the inverse or the iterated permutation. #R##N#In this paper we initiate the study of techniques that exploit the compressibility of the data itself, while retaining efficient computation of $\pi(i)$ and its inverse. #R##N#In particular, we focus on exploiting {\em runs}, which are subsets (contiguous or not) of the domain where the permutation is monotonic. #R##N#Several variants of those types of runs arise in real applications such as inverted indexes and suffix arrays. #R##N#Furthermore, our improved results on compressed data structures for permutations also yield better adaptive sorting algorithms.

Includes members:
  Member "succinct representations of permutations and functions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "path query data structures in practice")
  Member "lrm trees compressed indices adaptive sorting and compressed permutations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fully functional static and dynamic succinct trees")
  Member "compressed representations of permutations and applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "compression in the space of permutations")
  Member "optimal succinctness for range minimum queries":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "space efficient construction of lyndon arrays in linear time")
  Member "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "path query data structures in practice")
  Member "d ary bounded length huffman coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reserved length prefix coding")

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)