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: "fully functional suffix trees and optimal text searching in bwt runs bounded space"
  Abstract: Indexing highly repetitive texts --- such as genomic databases, software repositories and versioned text collections --- has become an important problem since the turn of the millennium. A relevant compressibility measure for repetitive texts is $r$, the number of runs in their Burrows-Wheeler Transforms (BWTs). One of the earliest indexes for repetitive collections, the Run-Length FM-index, used $O(r)$ space and was able to efficiently count the number of occurrences of a pattern of length $m$ in the text (in loglogarithmic time per pattern symbol, with current techniques). However, it was unable to locate the positions of those occurrences efficiently within a space bounded in terms of$r$. Since then, a number of other indexes with space bounded by other measures of repetitiveness --- the number of phrases in the Lempel-Ziv parse, the sizeof the smallest grammar generating (only) the text, the size of the smallest automaton recognizing the text factors --- have been proposed for efficiently locating,but not directly counting, the occurrences of a pattern. In this paper we close this long-standing problem, showing how to extend the Run-Length FM-index so that it can locate the $occ$ occurrences efficiently within $O(r)$ space (in loglogarithmic time each), and reaching optimal time $O(m+occ)$ within $O(r\log(n/r))$ space, on a RAM machine with words of $w=\Omega(\log n)$ bits. Within $O(r\log (n/r))$ space, our index can also count in optimal time $O(m)$.Raising the space to $O(r w\log_\sigma(n/r))$, we support count and locate in $O(\lceil m\log(\sigma)/w\rceil)$ and $O(\lceil m\log(\sigma)/w\rceil+occ)$ time, which is optimal in the packed setting and had not been obtained before in compressed space. We also describe a structure using $O(r\log(n/r))$ space that replaces the text and extracts any text substring ...

Connected through hyperedge HE-1 (induced by source paper "towards a definitive measure of repetitiveness"):
  with members:
    - "resolution of the burrows wheeler transform conjecture"
    - "optimal rank and select queries on dictionary compressed text"
    - "optimal time dictionary compressed indexes"
    - "on the approximation ratio of greedy parsings"
    - "universal compressed text indexing"
    - "representing the suffix tree with the cdawg"
    - "time space trade offs for lempel ziv compressed indexing"
    - "at the roots of dictionary compression string attractors"

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"
    - "universal compressed text indexing"
    - "time space trade offs for lempel ziv compressed indexing"
    - "optimal construction of compressed indexes for highly repetitive texts"
    - "at the roots of dictionary compression string attractors"
    - "queries on lz bounded encodings"

Connected through hyperedge HE-3 (induced by source paper "fast small and simple document listing on repetitive text collections"):
  with members:
    - "document listing on repetitive collections with guaranteed performance"
    - "optimal time text indexing in bwt runs bounded space"
    - "document retrieval on repetitive string collections"
    - "document retrieval on repetitive collections"
    - "a really simple approximation of smallest grammar"
    - "spaces trees and colors the algorithmic landscape of document retrieval on sequences"

Connected through hyperedge HE-4 (induced by source paper "refining the r index"):
  with members:
    - "conversion from rlbwt to lz77"
    - "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 construction of compressed indexes for highly repetitive texts"
    - "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)