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: "optimal trade off for succinct string indexes"
  Abstract: Let s be a string whose symbols are solely available through access(i), a read-only operation that probes s and returns the symbol at position i in s. Many compressed data structures for strings, trees, and graphs, require two kinds of queries on s: select(c, j), returning the position in s containing the jth occurrence of c, and rank(c, p), counting how many occurrences of c are found in the first p positions of s. We give matching upper and lower bounds for this problem, improving the lower bounds given by Golynski [Theor. Comput. Sci. 387 (2007)] [PhD thesis] and the upper bounds of Barbay et al. [SODA 2007]. We also present new results in another model, improving on Barbay et al. [SODA 2007] and matching a lower bound of Golynski [SODA 2009]. The main contribution of this paper is to introduce a general technique for proving lower bounds on succinct data structures, that is based on the access patterns of the supported operations, abstracting from the particular operations at hand. For this, it may find application to other interesting problems on succinct data structures.

Connected through hyperedge HE-1 (induced by source paper "grammar compressed sequences with rank select support"):
  with members:
    - "queries on lz bounded encodings"
    - "spaces trees and colors the algorithmic landscape of document retrieval on sequences"
    - "a succinct grammar compression"
    - "compact binary relation representations with rich functionality"
    - "data structure lower bounds on random access to grammar compressed strings"
    - "optimal lower and upper bounds for representing sequences"
    - "on compressing permutations and adaptive sorting"
    - "efficient fully compressed sequence representations"

Connected through hyperedge HE-2 (induced by source paper "range predecessor and lempel ziv parsing"):
  with members:
    - "faster lightweight lempel ziv parsing"
    - "wavelet trees meet suffix trees"
    - "linear time construction of compressed text indices in compact space"
    - "queries on lz bounded encodings"
    - "lightweight lempel ziv parsing"
    - "faster compact on line lempel ziv factorization"
    - "linear time lempel ziv factorization simple fast small"
    - "succinct indices for range queries with applications to orthogonal range maxima"

Connected through hyperedge HE-3 (induced by source paper "linear time construction of compressed text indices in compact space"):
  with members:
    - "combined data structure for previous and next smaller values"
    - "more haste less waste lowering the redundancy in fully indexable dictionaries"
    - "fully functional static and dynamic succinct trees"
    - "optimal succinctness for range minimum queries"

Connected through hyperedge HE-4 (induced by source paper "spaces trees and colors the algorithmic landscape of document retrieval on sequences"):
  with members:
    - "orthogonal range searching for text indexing"
    - "optimal top k document retrieval"
    - "on optimal top k string retrieval"
    - "faster compact top k document retrieval"
    - "new lower and upper bounds for representing sequences"
    - "towards an optimal space and query time index for top k document retrieval"
    - "space efficient data analysis queries on grids"
    - "new algorithms on wavelet trees and applications to information retrieval"

Connected through hyperedge HE-5 (induced by source paper "new lower and upper bounds for representing sequences"):
  with members:
    - "efficient fully compressed sequence representations"
    - "compressed representations of permutations and applications"
    - "fast in memory xpath search over compressed text and tree indexes"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "large alphabets and incompressibility"
    - "practical entropy compressed rank select dictionary"
    - "time space trade offs for predecessor search"

Connected through hyperedge HE-6 (induced by source paper "optimal lower and upper bounds for representing sequences"):
  with members:
    - "new lower and upper bounds for representing sequences"
    - "efficient fully compressed sequence representations"
    - "compressed representations of permutations and applications"
    - "fast in memory xpath search over compressed text and tree indexes"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"
    - "large alphabets and incompressibility"
    - "practical entropy compressed rank select dictionary"

Connected through hyperedge HE-7 (induced by source paper "towards an optimal space and query time index for top k document retrieval"):
  with members:
    - "top k color queries for document retrieval"
    - "range quantile queries another virtue of wavelet trees"
    - "optimal succinctness for range minimum queries"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-8 (induced by source paper "efficient fully compressed sequence representations"):
  with members:
    - "optimal dynamic sequence representations"
    - "new lower and upper bounds for representing sequences"
    - "on compressing permutations and adaptive sorting"
    - "succinct representations of permutations and functions"
    - "compressed representations of permutations and applications"
    - "more haste less waste lowering the redundancy in fully indexable dictionaries"
    - "a lower bound for succinct rank queries"
    - "worst case optimal adaptive prefix coding"

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)