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 "streaming periodicity with mismatches"):
  Abstract: We study the problem of finding all $k$-periods of a length-$n$ string $S$, presented as a data stream. $S$ is said to have $k$-period $p$ if its prefix of length $n-p$ differs from its suffix of length $n-p$ in at most $k$ locations. #R##N#We give a one-pass streaming algorithm that computes the $k$-periods of a string $S$ using $\text{poly}(k, \log n)$ bits of space, for $k$-periods of length at most $\frac{n}{2}$. We also present a two-pass streaming algorithm that computes $k$-periods of $S$ using $\text{poly}(k, \log n)$ bits of space, regardless of period length. We complement these results with comparable lower bounds.

Includes members:
  Member "streaming pattern matching with d wildcards":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sliding window property testing for regular languages")
  Member "tight tradeoffs for real time approximation of longest palindromes in streams":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "periodicity in data streams with wildcards")
  Member "streaming k mismatch with data recovery and applications":
    also connected through other hyperedges:
      (none)
  Member "dictionary matching in a stream":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sliding window property testing for regular languages")
  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")

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)