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: "at the roots of dictionary compression string attractors"
  Abstract: A well-known fact in the field of lossless text compression is that high-order entropy is a weak model when the input contains long repetitions. Motivated by this fact, decades of research have generated myriads of so-called dictionary compressors: algorithms able to reduce the text's size by exploiting its repetitiveness. Lempel-Ziv 77 is probably one of the most successful and known tools of this kind, followed by straight-line programs, run-length Burrows-Wheeler transform, macro schemes, collage systems, and the compact directed acyclic word graph. In this paper, we show that these techniques are only different solutions to the same, elegant, combinatorial problem: to find a small set of positions capturing all distinct text's substrings. We call \emph{string attractor} such a set. We first show reductions between dictionary compressors and string attractors. This gives us the approximation ratios of dictionary compressors with respect to the smallest string attractor and allows us to solve several open problems related to the asymptotic relations between the output sizes of different dictionary compressors. We then show that $k$-attractor problem --- that is, deciding whether a text has a size-$t$ set of positions capturing all substrings of length at most $k$ --- is NP-complete for $k\geq 3$. This, in particular, implies the NP-completeness of the full string attractor problem. We provide several approximation techniques for the smallest $k$-attractor, show that the problem is APX-complete for constant $k$, and give strong inapproximability results. To conclude, we provide matching lower- and upper- bounds for the random access problem on string attractors. Our data structure matching the lower bound is optimal also for LZ77, straight-line programs, collage systems, and macro schemes, and therefore essentially closes the random access problem for all these compressors.

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"
    - "representing the suffix tree with the cdawg"
    - "time space trade offs for lempel ziv compressed indexing"

Connected through hyperedge HE-2 (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"
    - "optimal construction of compressed indexes for highly repetitive texts"
    - "optimal time text indexing in bwt runs bounded space"
    - "space efficient construction of compressed indexes in deterministic linear time"

Connected through hyperedge HE-3 (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"
    - "optimal construction of compressed indexes for highly repetitive texts"
    - "queries on lz bounded encodings"

Connected through hyperedge HE-4 (induced by source paper "lempel ziv like parsing in small space"):
  with members:
    - "relations between greedy and bit optimal lz77 encodings"
    - "lz end parsing in compressed space"
    - "approximating lz77 via small space multiple pattern matching"
    - "from theory to practice plug and play with succinct data structures"
    - "lempel ziv parsing in external memory"
    - "linear time lempel ziv factorization simple fast small"
    - "relative lempel ziv factorization for efficient storage and retrieval of web collections"
    - "large alphabets and incompressibility"

Connected through hyperedge HE-5 (induced by source paper "bidirectional text compression in external memory"):
  with members:
    - "lzrr lz77 parsing with right reference"
    - "o n log n time text compression by lz style longest first substitution"
    - "compression with the tudocomp framework"
    - "lempel ziv decoding in external memory"
    - "lz end parsing in compressed space"
    - "lightweight lempel ziv parsing"
    - "lempel ziv parsing in external memory"
    - "simpler and faster lempel ziv factorization"

Connected through hyperedge HE-6 (induced by source paper "a new class of searchable and provably highly compressible string transformations"):
  with members:
    - "optimal time text indexing in bwt runs bounded space"
    - "large scale compression of genomic sequence databases with the burrows wheeler transform"
    - "optimal lower and upper bounds for representing sequences"
    - "a note on the burrows wheeler transformation"

Connected through hyperedge HE-7 (induced by source paper "the smallest grammar problem revisited"):
  with members:
    - "entropy bounds for grammar compression"
    - "a succinct grammar compression"
    - "approximation of grammar based compression via recompression"
    - "identifying hierarchical structure in sequences a linear time algorithm"

Connected through hyperedge HE-8 (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"

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)