human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a simple reduction for full permuted pattern matching problems on multi track strings"
  Abstract: In this paper we study a variant of string pattern matching which deals with tuples of strings known as \textit{multi-track strings}. Multi-track strings are a generalisation of strings (or \textit{single-track strings}) that have primarily found uses in problems related to searching multiple genomes and music information retrieval. A multi-track string $\mathcal{T} = (t_1, t_2, t_3, \ldots , t_N)$ of length $n$ and track count $N$ is a multi-set of $N$ strings of length $n$ with characters drawn from a common alphabet of size $\sigma_U$. Given two multi-track strings $\mathcal{T} = (t_1, t_2, t_3, \ldots , t_N)$ and $ \mathcal{P} = (p_1, p_2, p_3, \ldots , p_N)$ of length $n$ and track count $N$, there is a \textit{full-permuted-match} between $\mathcal{P}$ and $\mathcal{T}$ if $t_{r_i} = p_i$ for all $i \in \{1,2,3,\ldots N \}$ and some permutation $(r_1, r_2, r_3\ldots,r_N)$ of $(1, 2, 3,\ldots,N)$, we denote this $\mathcal{P}\asymp\mathcal{T}$. #R##N#Efficient algorithms for some full-permuted-match problems on multi-track strings have recently been presented. In this paper we show a reduction from a multi-track string of length $n$ and track count $N$ with alphabet size $\sigma_U$, to a single-track string of length $2n-1$ with alphabet size $\sigma_U^N$. Through this reduction we allow any string algorithm to be used on multi-track string problems using $\asymp$ as the match relation. For polynomial time algorithms on single-track strings of length $n$ there is a multiplicative penalty of not more than $\mathcal{O}(N)$-time for the same algorithm on mt-strings of length $n$ and track count $N$.

Question: Please tell me which class the center node 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)