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 "the streaming k mismatch problem"):
  Abstract: We consider the problem of approximate pattern matching in a stream. In the streaming $k$-mismatch problem, we must compute all Hamming distances between a pattern of length $n$ and successive $n$-length substrings of a longer text, as long as the Hamming distance is at most $k$. The twin challenges of streaming pattern matching derive from the need both to achieve small and typically sublinear working space and also to have fast guaranteed running time for every arriving symbol of the text. #R##N#As a preliminary step we first give a deterministic $O(k(\log \frac{n}{k} + \log |\Sigma|) )$-bit encoding of all the alignments with Hamming distance at most $k$ between a pattern and a text of length $O(n)$. (We denote the input alphabet by the symbol $\Sigma$.) This result, which provides a solution for a seemingly difficult combinatorial problem, may be of independent interest. We then go on to give an $O(k\log^3 n\log\frac{n}{k})$-time streaming algorithm for the $k$-mismatch streaming problem which uses only $O(k\log{n}\log\frac{n}{k})$ bits of space. The space usage is within logarithmic factors of optimal and approximately a factor of $k$ improvement over the previous record [Clifford et al., SODA 2016]

Includes members:
  Member "optimal trade offs for pattern matching with k mismatches":
    also connected through other hyperedges:
      (none)
  Member "streaming periodicity with mismatches":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "periodicity in data streams with wildcards")
  Member "streaming k mismatch with error correcting and applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "weighted shortest common supersequence problem revisited")
  Member "approximate hamming distance in a stream":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "approximating text to pattern hamming distances")
  Member "the k mismatch problem revisited":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximating text to pattern hamming distances")
  Member "space lower bounds for online pattern matching":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "periodicity in data streams with wildcards")
  Member "parameterized matching in the streaming model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "streaming pattern matching with d wildcards")

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)