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 with oracle new streaming algorithms for edit distance and lcs"):
  Abstract: The edit distance (ED) and longest common subsequence (LCS) are two fundamental problems which quantify how similar two strings are to one another. In this paper, we consider these problems in the streaming model where one string is available via oracle queries and the other string comes as a stream of characters. Our main contribution is a constant factor approximation algorithm in this setting for ED with memory $O(n^{\delta})$ for any $\delta > 0$. In addition to this, we present an upper bound of $\tilde O(\sqrt{n})$ on the memory needed to approximate ED or LCS within a factor $1+o(1)$ in our setting. All our algorithms run in a single pass. #R##N#For approximating ED within a constant factor, we discover yet another application of triangle inequality, this time in the context of streaming algorithms. Triangle inequality has been previously used to obtain subquadratic time approximation algorithms for ED. Our technique is novel and elegantly utilizes triangle inequality to save memory at the expense of an exponential increase in the runtime.

Includes members:
  Member "approximating lcs in linear time beating the sqrt n barrier":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "space efficient deterministic approximation of string measures")
  Member "dynamic time warping in strongly subquadratic time algorithms for the low distance regime and approximate evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximating the geometric edit distance")
  Member "sublinear algorithms for gap edit distance":
    also connected through other hyperedges:
      (none)
  Member "reducing approximate longest common subsequence to approximate edit distance":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "constant factor approximation of near linear edit distance in near linear time")
  Member "constant factor approximation of near linear edit distance in near linear time":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "space efficient deterministic approximation of string measures")
  Member "constant factor approximations to edit distance on far input pairs in nearly linear time":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "space efficient deterministic approximation of string measures")
  Member "approximating edit distance within constant factor in truly sub quadratic time":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximating lcs in linear time beating the sqrt n barrier")
  Member "on estimating edit distance alignment dimension reduction and embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic time warping in strongly subquadratic time algorithms for the low distance regime and approximate evaluation")

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)