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: "compressed dynamic range majority and minority data structures"
  Abstract: In the range $\alpha$-majority query problem, we are given a sequence $S[1..n]$ and a fixed threshold $\alpha \in (0, 1)$, and are asked to preprocess $S$ such that, given a query range $[i..j]$, we can efficiently report the symbols that occur more than $\alpha (j-i+1)$ times in $S[i..j]$, which are called the range $\alpha$-majorities. In this article we first describe a dynamic data structure that represents $S$ in compressed space --- $nH_k+ o(n\lg \sigma)$ bits for any $k = o(\log_{\sigma} n)$, where $\sigma$ is the alphabet size and $H_k \le H_0 \le \lg\sigma $ is the $k$-th order empirical entropy of $S$ --- and answers queries in $O \left(\frac{\log n}{\alpha \log \log n} \right)$ time while supporting insertions and deletions in $S$ in $O \left( \frac{\lg n}{\alpha} \right)$ amortized time. We then show how to modify our data structure to receive some $\beta \ge \alpha$ at query time and report the range $\beta$-majorities in $O \left( \frac{\log n}{\beta \log \log n} \right)$ time, without increasing the asymptotic space or update-time bounds. The best previous dynamic solution has the same query and update times as ours, but it occupies $O(n)$ words and cannot take advantage of being given a larger threshold $\beta$ at query time.  [ABSTRACT CLIPPED DUE TO LENGTH.]

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)