human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on the approximation ratio of greedy parsings"):
  Abstract: Shannon's entropy is a clear lower bound for statistical compression. The situation is not so well understood for dictionary-based compression. A plausible lower bound is b, the least number of phrases of a general bidirectional parse of a text, where phrases can be copied from anywhere else in the text. Since computing b is NP-complete, a popular gold standard is z, the number of phrases in the Lempel-Ziv parse of the text, which is the optimal one when phrases can be copied only from the left. While z can be computed in linear time with a greedy algorithm, almost nothing has been known for decades about its approximation ratio with respect to b. In this paper we prove that z = O(b log(n/b)), where n is the text length. We also show that the bound is tight as a function of n, by exhibiting a string family where z = {\Omega}(b log n). Our upper bound is obtained by building a run-length context-free grammar based on a locally consistent parsing of the text. Our lower bound is obtained by relating b with r, the number of equal-letter runs in the Burrows-Wheeler transform of the text. We proceed by observing that Lempel-Ziv is just one particular case of greedy parse, and introduce a new parse where phrases can only be copied from lexicographically smaller text locations. We prove that the size v of the smallest parse of this kind has properties similar to z, including the same approximation ratio with respect to b. Interestingly, we also show that v = O(r), whereas r = o(z) holds on some particular classes of strings. On our way, we prove other relevant bounds between compressibility measures.

Includes members:
  Member "optimal time dictionary compressed indexes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards a definitive measure of repetitiveness")
  Member "at the roots of dictionary compression string attractors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards a definitive measure of repetitiveness")
  Member "compression with the tudocomp framework":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "bidirectional text compression in external memory")
  Member "optimal time text indexing in bwt runs bounded space":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fast indexes for gapped pattern matching")
  Member "a separation between run length slps and lz77":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "comparison of lz77 type parsings")
  Member "fully dynamic data structure for lce queries in compressed space":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fully functional suffix trees and optimal text searching in bwt runs bounded space")
  Member "composite repetition aware data structures":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on extensions of maximal repeats in compressed strings")
  Member "factorizations of the fibonacci infinite word":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the sequence of open and closed prefixes of a sturmian word")

Question: Please tell me which class the source paper 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)