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 abelian longest common factor with and without rle"):
  Abstract: We consider the Abelian longest common factor problem in two scenarios: when input strings are uncompressed and are of size $n$, and when the input strings are run-length encoded and their compressed representations have size at most $m$. The alphabet size is denoted by $\sigma$. For the uncompressed problem, we show an $o(n^2)$-time and $\Oh(n)$-space algorithm in the case of $\sigma=\Oh(1)$, making a non-trivial use of tabulation. For the RLE-compressed problem, we show two algorithms: one working in $\Oh(m^2\sigma^2 \log^3 m)$ time and $\Oh(m (\sigma^2+\log^2 m))$ space, which employs line sweep, and one that works in $\Oh(m^3)$ time and $\Oh(m)$ space that applies in a careful way a sliding-window-based approach. The latter improves upon the previously known $\Oh(nm^2)$-time and $\Oh(m^4)$-time algorithms that were recently developed by Sugimoto et al.\ (IWOCA 2017) and Grabowski (SPIRE 2017), respectively.

Includes members:
  Member "computing abelian regularities on rle strings":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fast and simple jumbled indexing for binary rle strings")
  Member "clustered integer 3sum via additive combinatorics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "all non trivial variants of 3 ldt are equivalent")
  Member "algorithms for longest common abelian factors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the parikh de bruijn grid")
  Member "binary jumbled pattern matching via all pairs shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on prefix normal words and prefix normal forms")
  Member "new algorithms for binary jumbled pattern matching":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "binary jumbled string matching for highly run length compressible texts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on prefix normal words and prefix normal forms")
  Member "algorithms for jumbled pattern matching in strings":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generating a gray code for prefix normal words in amortized polylogarithmic time per 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)