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: "hypergraph two coloring in the streaming model"
  Abstract: We consider space-efficient algorithms for two-coloring $n$-uniform hypergraphs $H=(V,E)$ in the streaming model, when the hyperedges arrive one at a time. It is known that any such hypergraph with at most $0.7 \sqrt{\frac{n}{\ln n}} 2^n$ hyperedges has a two-coloring [Radhakrishnan & Srinivasan, RSA, 2000], which can be found deterministically in polynomial time, if allowed full access to the input. #R##N#1. Let $s^D(v, q, n)$ be the minimum space used by a deterministic one-pass streaming algorithm that on receiving an $n$-uniform hypergraph $H$ on $v$ vertices and $q$ hyperedges $(q \leq 0.7 \sqrt{\frac{n}{\ln n}} 2^n)$, produces a proper two-coloring of $H$. We show that $s^D(n^2, q, n) = \Omega(q/n)$. This shows that no efficient deterministic streaming algorithm can match the performance of the Radhakrishnan-Srinivasan algorithm. #R##N#2. Let $s^R(v, q,n)$ be the minimum space used by a randomized one-pass streaming algorithm that on receiving an $n$-uniform hypergraph $H$ on $v$ vertices and $q$ hyperedges with high probability produces a proper two-coloring of $H$ (or declares failure). We show that $s^R(v, \frac{1}{10}\sqrt{\frac{n}{\ln n}} 2^n, n) = O(v \log v)$ by giving an efficient randomized streaming algorithm. #R##N#3. We show that for any $4 \leq t \leq \frac{n^2}{2n-1}$, $s^R\left(\frac{n^2}{t}, 2^{n-2}\exp(\frac{t}{8}), n\right) = O(n^2/t)$; in particular, every $n$-uniform hypergraph with at most $\frac{n^2}{t}$ vertices and $ 2^{n-1}\exp(\frac{t}{8})$ hyperedges is two-colorable. This shows that every non-two-colorable hypergraph on $o(n^2)$ vertices has $\omega(n^22^n)$ hyperedges. #R##N#The above results are inspired by the study of the number $q(n)$, the minimum possible number of hyperedges in a $n$-uniform hypergraph that is not two-colorable. It is known that $q(n) = \Omega(\sqrt{\frac{n}{\ln n}})$ [Radhakrishnan-Srinivasan] and $ q(n)= O(n^2 2^n)$ [Erdos, 1963].

Connected through hyperedge HE-1 (induced by source paper "graph coloring via degeneracy in streaming and other space conscious models"):
  with members:
    - "simple graph coloring algorithms for congested clique and massively parallel computation"
    - "greedy and local ratio algorithms in the mapreduce model"
    - "dynamic algorithms for graph coloring"
    - "dynamic graph coloring"
    - "simple and near optimal distributed coloring for sparse graphs"
    - "densest subgraph in dynamic graph streams"
    - "local conflict coloring"
    - "communication steps for parallel query processing"

Connected through hyperedge HE-2 (induced by source paper "coloring in graph streams"):
  with members:
    - "densest subgraph in dynamic graph streams"
    - "the locality of distributed symmetry breaking"
    - "densest subgraph in streaming and mapreduce"

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)