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 "lcsk practical similarity metric for long strings"):
  Abstract: In this paper we present $LCSk$++: a new metric for measuring the similarity of long strings, and provide an algorithm for its efficient computation. With ever increasing size of strings occuring in practice, e.g. large genomes of plants and animals, classic algorithms such as Longest Common Subsequence (LCS) fail due to demanding computational complexity. Recently, Benson et al. defined a similarity metric named $LCSk$. By relaxing the requirement that the $k$-length substrings should not overlap, we extend their definition into a new metric. An efficient algorithm is presented which computes $LCSk$++ with complexity of $O((|X|+|Y|)\log(|X|+|Y|))$ for strings $X$ and $Y$ under a realistic random model. The algorithm has been designed with implementation simplicity in mind. Additionally, we describe how it can be adjusted to compute $LCSk$ as well, which gives an improvement of the $O(|X|\dot|Y|)$ algorithm presented in the original $LCSk$ paper.

Includes members:
  Member "longest common subsequence in k length substrings":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "longest common subsequence in at least k length order isomorphic substrings")
  Member "efficient algorithms for the longest common subsequence in k length substrings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fast and simple algorithms for computing both lcs_ k and lcs_ k")
  Member "plagiarism detection using rouge and wordnet":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fast and simple algorithms for computing both lcs_ k and lcs_ k")

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)