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: "efficient fully compressed sequence representations"
  Abstract: We present a data structure that stores a sequence $s[1..n]$ over alphabet $[1..\sigma]$ in $n\Ho(s) + o(n)(\Ho(s){+}1)$ bits, where $\Ho(s)$ is the zero-order entropy of $s$. This structure supports the queries \access, \rank\ and \select, which are fundamental building blocks for many other compressed data structures, in worst-case time $\Oh{\lg\lg\sigma}$ and average time $\Oh{\lg \Ho(s)}$. The worst-case complexity matches the best previous results, yet these had been achieved with data structures using $n\Ho(s)+o(n\lg\sigma)$ bits. On highly compressible sequences the $o(n\lg\sigma)$ bits of the redundancy may be significant compared to the the $n\Ho(s)$ bits that encode the data. Our representation, instead, compresses the redundancy as well. Moreover, our average-case complexity is unprecedented. Our technique is based on partitioning the alphabet into characters of similar frequency. The subsequence corresponding to each group can then be encoded using fast uncompressed representations without harming the overall compression ratios, even in the redundancy. The result also improves upon the best current compressed representations of several other data structures. For example, we achieve $(i)$ compressed redundancy, retaining the best time complexities, for the smallest existing full-text self-indexes; $(ii)$ compressed permutations $\pi$ with times for $\pi()$ and $\pii()$ improved to loglogarithmic; and $(iii)$ the first compressed representation of dynamic collections of disjoint sets. We also point out various applications to inverted indexes, suffix arrays, binary relations, and data compressors. ...

Connected through hyperedge HE-1 (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"
    - "succinct representations of dynamic strings"
    - "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-2 (induced by source paper "fast compressed self indexes with deterministic linear time construction"):
  with members:
    - "fast prefix search in little space with applications"
    - "linear time string indexing and analysis in small space"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "deterministic indexing for packed strings"
    - "linear time construction of compressed text indices in compact space"
    - "suffix trays and suffix trists structures for faster text indexing"
    - "alphabet dependent string searching with wexponential search trees"
    - "optimal lower and upper bounds for representing sequences"

Connected through hyperedge HE-3 (induced by source paper "text indexing and searching in sublinear time"):
  with members:
    - "orthogonal point location and rectangle stabbing queries in 3 d"
    - "fast compressed self indexes with deterministic linear time construction"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "sparse suffix tree construction in optimal time and space"
    - "deterministic indexing for packed strings"
    - "range predecessor and lempel ziv parsing"
    - "wavelet trees meet suffix trees"
    - "suffix trays and suffix trists structures for faster text indexing"

Connected through hyperedge HE-4 (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"
    - "optimal trade off for succinct string indexes"

Connected through hyperedge HE-5 (induced by source paper "run compressed rank select for large alphabets"):
  with members:
    - "optimal time text indexing in bwt runs bounded space"
    - "from theory to practice plug and play with succinct data structures"
    - "new lower and upper bounds for representing sequences"
    - "optimal lower and upper bounds for representing sequences"

Connected through hyperedge HE-6 (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"
    - "dynamic data structures for document collections and graphs"
    - "linear time construction of compressed text indices in compact space"
    - "optimal dynamic sequence representations"
    - "more haste less waste lowering the redundancy in fully indexable dictionaries"
    - "fully functional static and dynamic succinct trees"

Connected through hyperedge HE-7 (induced by source paper "dynamic data structures for document collections and graphs"):
  with members:
    - "optimal top k document retrieval"
    - "optimal dynamic sequence representations"
    - "succinct representations of dynamic strings"
    - "fully functional static and dynamic succinct trees"
    - "dynamic ordered sets with exponential search trees"

Connected through hyperedge HE-8 (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"
    - "succinct representations of dynamic strings"
    - "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"

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)