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: "representing the suffix tree with the cdawg"
  Abstract: Given a string $T$, it is known that its suffix tree can be represented using the compact directed acyclic word graph (CDAWG) with $e_T$ arcs, taking overall $O(e_T+e_{{\overline{T}}})$ words of space, where ${\overline{T}}$ is the reverse of $T$, and supporting some key operations in time between $O(1)$ and $O(\log{\log{n}})$ in the worst case. This representation is especially appealing for highly repetitive strings, like collections of similar genomes or of version-controlled documents, in which $e_T$ grows sublinearly in the length of $T$ in practice. In this paper we augment such representation, supporting a number of additional queries in worst-case time between $O(1)$ and $O(\log{n})$ in the RAM model, without increasing space complexity asymptotically. Our technique, based on a heavy path decomposition of the suffix tree, enables also a representation of the suffix array, of the inverse suffix array, and of $T$ itself, that takes $O(e_T)$ words of space, and that supports random access in $O(\log{n})$ time. Furthermore, we establish a connection between the reversed CDAWG of $T$ and a context-free grammar that produces $T$ and only $T$, which might have independent interest.

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"
    - "fully functional suffix trees and optimal text searching in bwt runs bounded space"
    - "on the approximation ratio of greedy parsings"
    - "universal compressed text indexing"
    - "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 "fully functional bidirectional burrows wheeler indexes"):
  with members:
    - "simulating the dna string graph in succinct space"
    - "assembling omnitigs using hidden order de bruijn graphs"
    - "fast label extraction in the cdawg"
    - "linear time string indexing and analysis in small space"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "linear time construction of compressed text indices in compact space"
    - "variable order de bruijn graphs"
    - "engineering small space dictionary matching"

Connected through hyperedge HE-3 (induced by source paper "faster repetition aware compressed suffix trees based on block trees"):
  with members:
    - "optimal time text indexing in bwt runs bounded space"
    - "queries on lz bounded encodings"
    - "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-4 (induced by source paper "fully functional suffix trees and optimal text searching in bwt runs bounded space"):
  with members:
    - "resolution of the burrows wheeler transform conjecture"
    - "faster repetition aware compressed suffix trees based on block trees"
    - "optimal time dictionary compressed indexes"
    - "fast prefix search in little space with applications"
    - "efficient construction of a complete index for pan genomics read alignment"
    - "on the approximation ratio of greedy parsings"
    - "universal compressed text indexing"
    - "prefix free parsing for building big bwts"

Connected through hyperedge HE-5 (induced by source paper "optimal time dictionary compressed indexes"):
  with members:
    - "optimal rank and select queries on dictionary compressed text"
    - "fast prefix search in little space with applications"
    - "universal compressed text indexing"
    - "time space trade offs for lempel ziv compressed indexing"
    - "at the roots of dictionary compression string attractors"
    - "compressed indexing with signature grammars"
    - "document listing on repetitive collections with guaranteed performance"
    - "optimal time text indexing in bwt runs bounded space"

Connected through hyperedge HE-6 (induced by source paper "mr repair grammar compression based on maximal repeats"):
  with members:
    - "linear size cdawg new repetition aware indexing and grammar compression"
    - "fast label extraction in the cdawg"
    - "scalable partial least squares regression on grammar compressed data matrices"
    - "space efficient re pair compression"
    - "composite repetition aware data structures"

Connected through hyperedge HE-7 (induced by source paper "at the roots of dictionary compression string attractors"):
  with members:
    - "time space trade offs for lempel ziv compressed indexing"
    - "fast label extraction in the cdawg"
    - "optimal time text indexing in bwt runs bounded space"
    - "space efficient construction of compressed indexes in deterministic linear time"
    - "fully dynamic data structure for lce queries in compressed space"
    - "composite repetition aware data structures"
    - "linear time construction of compressed text indices in compact space"
    - "queries on lz bounded encodings"

Connected through hyperedge HE-8 (induced by source paper "fast label extraction in the cdawg"):
  with members:
    - "linear size cdawg new repetition aware indexing and grammar compression"
    - "traversing grammar compressed trees with constant delay"
    - "composite repetition aware data structures"
    - "large alphabets and incompressibility"

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)