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 "fully functional static and dynamic succinct trees"):
  Abstract: We propose new succinct representations of ordinal trees, which have been studied extensively. It is known that any $n$-node static tree can be represented in $2n + o(n)$ bits and a number of operations on the tree can be supported in constant time under the word-RAM model. However the data structures are complicated and difficult to dynamize. We propose a simple and flexible data structure, called the range min-max tree, that reduces the large number of relevant tree operations considered in the literature to a few primitives that are carried out in constant time on sufficiently small trees. The result is extended to trees of arbitrary size, achieving $2n + O(n /\polylog(n))$ bits of space. The redundancy is significantly lower than any previous proposal. Our data structure builds on the range min-max tree to achieve $2n+O(n/\log n)$ bits of space and $O(\log n)$ time for all the operations. We also propose an improved data structure using $2n+O(n\log\log n/\log n)$ bits and improving the time to the optimal $O(\log n/\log \log n)$ for most operations. Furthermore, we support sophisticated operations that allow attaching and detaching whole subtrees, in time $\Order(\log^{1+\epsilon} n / \log\log n)$. Our techniques are of independent interest. One allows representing dynamic bitmaps and sequences supporting rank/select and indels, within zero-order entropy bounds and optimal time $O(\log n / \log\log n)$ for all operations on bitmaps and polylog-sized alphabets, and $O(\log n \log \sigma / (\log\log n)^2)$ on larger alphabet sizes $\sigma$. This improves upon the best existing bounds for entropy-bounded storage of dynamic sequences, compressed full-text self-indexes, and compressed-space construction of the Burrows-Wheeler transform.

Includes members:
  Member "optimal dynamic sequence representations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "o log log n worst case local decoding and update efficiency for data compression")
  Member "lrm trees compressed indices adaptive sorting and compressed permutations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on compressing permutations and adaptive sorting")
  Member "succinct representations of dynamic strings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "compressed dynamic range majority and minority data structures")
  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 "logarithmic lower bounds in the cell probe model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "coarse grained complexity for dynamic algorithms")
  Member "orderly spanning trees with applications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "drawing planar graphs with few segments on a polynomial grid")

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)