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: "an algebraic 1 375 approximation algorithm for the transposition distance problem"
  Abstract: In genome rearrangements, the mutational event \emph{transposition} swaps two adjacent blocks of genes in one chromosome. The \emph{Transposition Distance Problem} (TDP) aims to find the minimum number of transpositions (distance) required to transform one chromosome into another, both represented as permutations. Setting the target permutation as the identity permutation, makes the TDP equivalent to the problem of \emph{Sorting by Transpositions} (SBT). #R##N#TDP is $\mathcal{NP}$-hard and the best approximation algorithm with a $1.375$ ratio was proposed in 2006 by Elias and Hartman. Their algorithm employs a technique called \emph{simplification} to transform an input permutation $\pi$ into a \emph{simple permutation} $\hat{\pi}$, obtained by inserting new symbols into $\pi$ in a way that the lower bound of the transposition distance of $\pi$ is kept on $\hat{\pi}$. The assumption is that handling with simple permutations is easier than with normal ones. A sequence of transpositions sorting $\hat{\pi}$ can be mimicked to sort $\pi$. #R##N#In this work, we first show that the algorithm of Elias and Hartman may require one transposition above the intended approximation ratio of $1.375$, depending on how the input permutation is simplified. Then, we propose a new $1.375$-approximation algorithm to solve TDP based on an algebraic formalism which does not use simplification, ensuring the approximation ratio of $1.375$ for all the permutations in the Symmetric Group $S_n$. We also propose a new upper bound for the transposition distance. #R##N#Implementations of our algorithm and the one of Elias and Hartman were audited using GRAAu tool. The results show that, taking as input short permutations with maximum length $13$, in addition to keeping the approximation below the $1.375$ ratio, our algorithm returns a higher percentage of exact distances than the one of Elias and Hartman.

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)