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 "binary jumbled string matching for highly run length compressible texts"):
  Abstract: The Binary Jumbled String Matching Problem is defined as follows: Given a string s over {a,b} of length n and a query (x,y), with x,y non-negative integers, decide whether s has a substring t with exactly x [email protected]?s and y [email protected]?s. Previous solutions created an index of size O(n) in a pre-processing step, which was then used to answer queries in constant time. The fastest algorithms for construction of this index have running time O(n^2/logn) (Burcsi et al., 2010 [1]; Moosa and Rahman, 2010 [7]), or O(n^2/log^2n) in the word-RAM model (Moosa and Rahman, 2012 [8]). We propose an index constructed directly from the run-length encoding of s. The construction time of our index is O([email protected]^[email protected]), where O(n) is the time for computing the run-length encoding of s and @r is the length of this encoding-this is no worse than previous solutions if @r=O(n/logn) and better if @r=o(n/logn). Our index L can be queried in O([email protected]) time. While |L|=O(min(n,@r^2)) in the worst case, preliminary investigations have indicated that |L| may often be close to @r. Furthermore, the algorithm for constructing the index is conceptually simple and easy to implement. In an attempt to shed light on the structure and size of our index, we characterize it in terms of the prefix normal forms of s introduced in Fici and Liptak (2011) [6].

Includes members:
  Member "algorithms for jumbled pattern matching in strings":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "generating a gray code for prefix normal words in amortized polylogarithmic time per word")
  Member "on prefix normal words":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "generating a gray code for prefix normal words in amortized polylogarithmic time per word")

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)