human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "dynamic data structures for document collections and graphs"
  Abstract: In the dynamic indexing problem, we must maintain a changing collection of text documents so that we can efficiently support insertions, deletions, and pattern matching queries. We are especially interested in developing efficient data structures that store and query the documents in compressed form. All previous compressed solutions to this problem rely on answering rank and select queries on a dynamic sequence of symbols. Because of the lower bound in [Fredman and Saks, 1989], answering rank queries presents a bottleneck in compressed dynamic indexing. In this paper we show how this lower bound can be circumvented using our new framework. We demonstrate that the gap between static and dynamic variants of the indexing problem can be almost closed. Our method is based on a novel framework for adding dynamism to static compressed data structures. Our framework also applies more generally to dynamizing other problems. We show, for example, how our framework can be applied to develop compressed representations of dynamic graphs and binary relations.

Connected through hyperedge HE-1 (induced by source paper "on dynamic succinct graph representations"):
  with members:
    - "faster dynamic compressed d ary relations"
    - "compressed representation of dynamic binary relations with applications"
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"

Connected through hyperedge HE-2 (induced by source paper "fast and compact planar embeddings"):
  with members:
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"
    - "fully functional static and dynamic succinct trees"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "practical entropy compressed rank select dictionary"
    - "orderly spanning trees with applications"
    - "dynamic generators of topologically embedded graphs"
    - "compact encodings of planar graphs via canonical orderings and multiple parentheses"
    - "linear time succinct encodings of planar graphs via canonical orderings"

Connected through hyperedge HE-3 (induced by source paper "space efficient construction of compressed indexes in deterministic linear time"):
  with members:
    - "linear time string indexing and analysis in small space"
    - "range predecessor and lempel ziv parsing"
    - "linear time construction of compressed text indices in compact space"
    - "optimal dynamic sequence representations"
    - "efficient fully compressed sequence representations"
    - "more haste less waste lowering the redundancy in fully indexable dictionaries"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-4 (induced by source paper "dynamic index and lz factorization in compressed space"):
  with members:
    - "fully dynamic data structure for lce queries in compressed space"
    - "online self indexed grammar compression"
    - "improved esp index a practical self index for highly repetitive texts"
    - "restructuring compressed texts without explicit decompression"

Connected through hyperedge HE-5 (induced by source paper "dynamic index lz factorization and lce queries in compressed space"):
  with members:
    - "online self indexed grammar compression"
    - "approximating lz77 via small space multiple pattern matching"
    - "finger search random access and longest common extensions in grammar compressed strings"
    - "fingerprints in compressed strings"
    - "restructuring compressed texts without explicit decompression"

Question: Please tell me which class the center node 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)