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: "word packing algorithms for dynamic connectivity and dynamic sets"
  Abstract: We examine several (dynamic) graph and set intersection problems in the word-RAM model with word size $w$. We begin with Dynamic Connectivity where we need to maintain a fully dynamic graph $G=(V,E)$ with $n=|V|$ vertices while supporting $(s,t)$-connectivity queries. To do this, we provide a new simplified worst-case solution for the famous Dynamic Connectivity (which is interesting on its own merit), and then show how in the word-RAM model the query and update cost can be reduced to $O(\sqrt{n\frac{\log n}{w}\log(\frac{w}{\log n})})$, assuming $w < n^{1-\Omega(1)}$. Since $w=\Omega(\log n)$, this bound is always $O(\sqrt{n})$ and it is $o(\sqrt{n})$ when $w=\omega(\log n)$. #R##N#We then examine the task of maintaining a family $F$ of dynamic sets where insertions and deletions into the sets are allowed, while enabling a set intersection reporting queries on sets from $F$. We first show that given a known upper-bound $d$ on the size of any set, we can maintain $F$ so that a set intersection reporting query costs $O(\frac{d}{w/log^2 w})$ expected time, and updates cost $O(\log w)$ expected time. Using this algorithm we can list all triangles of a graph $G=(V,E)$ in $O(\frac{m\alpha}{w/log^2 w} +t)$ expected time where $m=|E|$, $\alpha$ is the arboricity of $G$, and $t$ is the size of the output. This is comparable with known algorithms that run in $O(m \alpha)$ time. #R##N#Next, we provide an incremental data structure on $F$ that supports intersection proof queries where two sets that intersect must return an element in the intersection. Both queries and insertions of elements into sets take $O(\sqrt \frac{N}{w/log^2 w})$ expected time, where $N=\sum_{S\in F} |S|$. Finally, we provide time/space tradeoffs for the fully dynamic set intersection listing problem.

Connected through hyperedge HE-1 (induced by source paper "data structure lower bounds for document indexing problems"):
  with members:
    - "clustered integer 3sum via additive combinatorics"
    - "space efficient string indexing for wildcard pattern matching"
    - "popular conjectures imply strong lower bounds for dynamic problems"
    - "dictionary matching with one gap"
    - "higher lower bounds from the 3sum conjecture"
    - "orthogonal range searching on the ram revisited"
    - "string indexing for patterns with wildcards"
    - "on the hardness of distance oracle for sparse graph"

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)