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 "optimal computation of avoided words"):
  Abstract: The deviation of the observed frequency of a word w from its expected frequency in a given sequence x is used to determine whether or not the word is avoided. This concept is particularly useful in DNA linguistic analysis. The value of the standard deviation of w, denoted by std(w), effectively characterises the extent of a word by its edge contrast in the context in which it occurs. A word w of length k > 2 is a ρ-avoided word in x if std(w) ≤ ρ, for a given threshold ρ < 0. Notice that such a word may be completely absent from x. Hence computing all such words naively can be a very time-consuming procedure, in particular for large k. In this article, we propose an O(n)-time and O(n)-space algorithm to compute all ρ-avoided words of length k in a given sequence x of length n over a fixed-sized alphabet. We also present a time-optimal O(σn)-time and O(σn)-space algorithm to compute all ρ-avoided words (of any length) in a sequence of length n over an alphabet of size σ. Furthermore, we provide a tight asymptotic upper bound for the number of ρ-avoided words and the expected length of the longest one. We make available an open-source implementation of our algorithm. Experimental results, using both real and synthetic data, show the efficiency of our implementation.

Includes members:
  Member "space efficient detection of unusual words":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a framework for space efficient string kernels")
  Member "linear time computation of minimal absent words using suffix array":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "minimal absent words in rooted and unrooted trees")
  Member "weighted ancestors in suffix trees":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "algorithms for anti powers in strings")

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)