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 in place suffix sorting"
  Abstract: The suffix array is a fundamental data structure for many applications that involve string searching and data compression. Designing time/space-efficient suffix array construction algorithms has attracted significant attentions and considerable advances have been made in the last 20 years. We obtain the \emph{first} in-place suffix array construction algorithms that are optimal both in time and space for (read-only) integer alphabets. Concretely, we make the following contributions: #R##N#1. For the integer alphabets, we obtain the first suffix sorting algorithm which takes linear time and uses only $O(1)$ workspace (the workspace is the space needed beyond the input string and the output suffix array). The input string may be modified during the execution of the algorithm. Our C implementation of the algorithm requires only 8 Bytes of the workspace. #R##N#2. We strengthen the first result by providing the first linear time in-place algorithm for read-only integer alphabets with $|\Sigma|=O(n)$ (i.e., the input string cannot be modified). This algorithm settles the open problem posed by [Franceschini and Muthukrishnan, ICALP'07]. The open problem asked to design in-place algorithms in $o(n\log n)$ time and ultimately, in $O(n)$ time for (read-only) integer alphabets with $|\Sigma| \leq n$. Our result is in fact slightly stronger since we allow $|\Sigma|=O(n)$. #R##N#3. Besides, for the read-only general alphabets (i.e., only comparisons are allowed), we present an optimal $O(n\log n)$ time in-place suffix sorting algorithm, recovering the result obtained by Franceschini and Muthukrishnan which was an open problem posed by [Manzini and Ferragina, ESA'02].

Connected through hyperedge HE-1 (induced by source paper "re pair in place"):
  with members:
    - "a study for image compression using re pair algorithm"
    - "a faster external memory priority queue with decreasekeys"
    - "mr repair grammar compression based on maximal repeats"
    - "repair in compressed space and time"
    - "burrows wheeler transform and lcp array construction in constant space"
    - "practical and effective re pair compression"
    - "optimal time and space construction of suffix arrays and lcp arrays for integer alphabets"
    - "scalable partial least squares regression on grammar compressed data matrices"

Connected through hyperedge HE-2 (induced by source paper "optimal time and space construction of suffix arrays and lcp arrays for integer alphabets"):
  with members:
    - "fast q gram mining on slp compressed strings"

Connected through hyperedge HE-3 (induced by source paper "in place longest common extensions"):
  with members:
    - "small space encoding lce data structure with constant time queries"
    - "burrows wheeler transform and lcp array construction in constant space"
    - "optimal time and space construction of suffix arrays and lcp arrays for integer alphabets"
    - "fast longest common extensions in small space"
    - "tight lower bounds for the longest common extension problem"
    - "dynamic index lz factorization and lce queries in compressed space"
    - "longest common extensions in sublinear space"
    - "searching of gapped repeats and subrepetitions in a word"

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)