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: "succinct representations of dynamic strings"
  Abstract: The rank and select operations over a string of length n from an alphabet of size $\sigma$ have been used widely in the design of succinct data structures. In many applications, the string itself need be maintained dynamically, allowing characters of the string to be inserted and deleted. Under the word RAM model with word size $w=\Omega(\lg n)$, we design a succinct representation of dynamic strings using $nH_0 + o(n)\lg\sigma + O(w)$ bits to support rank, select, insert and delete in $O(\frac{\lg n}{\lg\lg n}(\frac{\lg \sigma}{\lg\lg n}+1))$ time. When the alphabet size is small, i.e. when $\sigma = O(\polylog (n))$, including the case in which the string is a bit vector, these operations are supported in $O(\frac{\lg n}{\lg\lg n})$ time. Our data structures are more efficient than previous results on the same problem, and we have applied them to improve results on the design and construction of space-efficient text indexes.

Connected through hyperedge HE-1 (induced by source paper "compressed dynamic range majority and minority data structures"):
  with members:
    - "optimal query time for encoding range majority"
    - "range majorities and minorities in arrays"
    - "compressed dynamic range majority data structures"
    - "compressed data structures for dynamic sequences"
    - "optimal encodings for range majority queries"
    - "better space bounds for parameterized range majority and minority"
    - "optimal lower and upper bounds for representing sequences"
    - "dynamic range majority data structures"

Connected through hyperedge HE-2 (induced by source paper "lyndon array construction during burrows wheeler inversion"):
  with members:
    - "algorithms to compute the lyndon array"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "simpler and faster lempel ziv factorization"
    - "efficient fully compressed sequence representations"
    - "fully functional static and dynamic succinct trees"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-3 (induced by source paper "succinct choice dictionaries"):
  with members:
    - "dynamic integer sets with optimal rank select and predecessor search"
    - "succinct representations of permutations and functions"
    - "fully functional static and dynamic succinct trees"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "logarithmic lower bounds in the cell probe model"
    - "dynamic ordered sets with exponential search trees"

Connected through hyperedge HE-4 (induced by source paper "compressed data structures for dynamic sequences"):
  with members:
    - "on line indexing for general alphabets via predecessor queries on subsets of an ordered list"
    - "optimal dynamic sequence representations"
    - "new lower and upper bounds for representing sequences"
    - "succinct representations of permutations and functions"
    - "cram compressed random access memory"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-5 (induced by source paper "dynamic data structures for document collections and graphs"):
  with members:
    - "optimal top k document retrieval"
    - "optimal dynamic sequence representations"
    - "efficient fully compressed sequence representations"
    - "fully functional static and dynamic succinct trees"
    - "dynamic ordered sets with exponential search trees"

Connected through hyperedge HE-6 (induced by source paper "efficient compressed wavelet trees over large alphabets"):
  with members:
    - "optimal dynamic sequence representations"
    - "new lower and upper bounds for representing sequences"
    - "on compressing permutations and adaptive sorting"
    - "new algorithms on wavelet trees and applications to information retrieval"
    - "efficient fully compressed sequence representations"
    - "range quantile queries another virtue of wavelet trees"
    - "fully functional static and dynamic succinct trees"
    - "fast in memory xpath search over compressed text and tree indexes"

Connected through hyperedge HE-7 (induced by source paper "optimal dynamic sequence representations"):
  with members:
    - "new lower and upper bounds for representing sequences"
    - "a dynamic stabbing max data structure with sub logarithmic query time"
    - "fixed block compression boosting in fm indexes"
    - "compressed representations of permutations and applications"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-8 (induced by source paper "space efficient data analysis queries on grids"):
  with members:
    - "orthogonal range searching on the ram revisited"
    - "new algorithms on wavelet trees and applications to information retrieval"
    - "range quantile queries another virtue of wavelet trees"
    - "fully functional static and dynamic succinct trees"
    - "optimal succinctness for range minimum queries"
    - "searching for frequent colors in rectangles"
    - "practical entropy compressed rank select dictionary"

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)