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 construction of compressed indexes for highly repetitive texts"
  Abstract: We propose algorithms that, given the input string of length $n$ over integer alphabet of size $\sigma$, construct the Burrows-Wheeler transform (BWT), the permuted longest-common-prefix (PLCP) array, and the LZ77 parsing in $O(n/\log_{\sigma}n+r\,{\rm polylog}\,n)$ time and working space, where $r$ is the number of runs in the BWT of the input. These are the essential components of many compressed indexes such as compressed suffix tree, FM-index, and grammar and LZ77-based indexes, but also find numerous applications in sequence analysis and data compression. The value of $r$ is a common measure of repetitiveness that is significantly smaller than $n$ if the string is highly repetitive. Since just accessing every symbol of the string requires $\Omega(n/\log_{\sigma}n)$ time, the presented algorithms are time and space optimal for inputs satisfying the assumption $n/r\in\Omega({\rm polylog}\,n)$ on the repetitiveness. For such inputs our result improves upon the currently fastest general algorithms of Belazzougui (STOC 2014) and Munro et al. (SODA 2017) which run in $O(n)$ time and use $O(n/\log_{\sigma} n)$ working space. We also show how to use our techniques to obtain optimal solutions on highly repetitive data for other fundamental string processing problems such as: Lyndon factorization, construction of run-length compressed suffix arrays, and some classical "textbook" problems such as computing the longest substring occurring at least some fixed number of times.

Connected through hyperedge HE-1 (induced by source paper "on the complexity of bwt runs minimization via alphabet reordering"):
  with members:
    - "on the hardness and inapproximability of recognizing wheeler graphs"
    - "resolution of the burrows wheeler transform conjecture"
    - "string synchronizing sets sublinear time bwt construction and optimal lce data structure"
    - "tunneling on wheeler graphs"
    - "efficient construction of a complete index for pan genomics read alignment"
    - "at the roots of dictionary compression string attractors"
    - "optimal time text indexing in bwt runs bounded space"
    - "space efficient construction of compressed indexes in deterministic linear time"

Connected through hyperedge HE-2 (induced by source paper "resolution of the burrows wheeler transform conjecture"):
  with members:
    - "towards a definitive measure of repetitiveness"
    - "optimal rank and select queries on dictionary compressed text"
    - "optimal time dictionary compressed indexes"
    - "fully functional suffix trees and optimal text searching in bwt runs bounded space"
    - "universal compressed text indexing"
    - "time space trade offs for lempel ziv compressed indexing"
    - "at the roots of dictionary compression string attractors"
    - "queries on lz bounded encodings"

Connected through hyperedge HE-3 (induced by source paper "string synchronizing sets sublinear time bwt construction and optimal lce data structure"):
  with members:
    - "quasi linear time algorithm for longest common circular factor"
    - "locally consistent parsing for text indexing in small space"
    - "text indexing and searching in sublinear time"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "wavelet trees meet suffix trees"
    - "linear time construction of compressed text indices in compact space"
    - "internal pattern matching queries in a text and applications"
    - "recompression a simple and powerful technique for word equations"

Connected through hyperedge HE-4 (induced by source paper "compact data structures for shortest unique substring queries"):
  with members:
    - "a faster implementation of online run length burrows wheeler transform"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "an in place framework for exact and approximate shortest unique substring queries"
    - "succinct representations of permutations and functions"

Connected through hyperedge HE-5 (induced by source paper "conversion from rlbwt to lz77"):
  with members:
    - "repair in compressed space and time"
    - "dynamic relative compression dynamic partial sums and substring concatenation"
    - "a really simple approximation of smallest grammar"
    - "alphabet dependent string searching with wexponential search trees"

Connected through hyperedge HE-6 (induced by source paper "refining the r index"):
  with members:
    - "conversion from rlbwt to lz77"
    - "fully functional suffix trees and optimal text searching in bwt runs bounded space"
    - "lower bounds for text indexing with mismatches and differences"
    - "efficient construction of a complete index for pan genomics read alignment"
    - "prefix free parsing for building big bwts"
    - "from lz77 to the run length encoded burrows wheeler transform and back"
    - "a framework of dynamic data structures for string processing"
    - "optimal time text indexing in bwt runs bounded space"

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)