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: "all maximal independent sets and dynamic dominance for sparse graphs"
  Abstract: We describe algorithms, based on Avis and Fukuda's reverse search paradigm, for listing all maximal independent sets in a sparse graph in polynomial time and delay per output. For bounded degree graphs, our algorithms take constant time per set generated; for minor-closed graph families, the time is O(n) per set, and for more general sparse graph families we achieve subquadratic time per set. We also describe new data structures for maintaining a dynamic vertex set S in a sparse or minor-closed graph family, and querying the number of vertices not dominated by S; for minor-closed graph families the time per update is constant, while it is sublinear for any sparse graph family. We can also maintain a dynamic vertex set in an arbitrary m-edge graph and test the independence of the maintained set in time O(sqrt m) per update. We use the domination data structures as part of our enumeration algorithms.

Connected through hyperedge HE-1 (induced by source paper "a tutorial on clique problems in communications and signal processing"):
  with members:
    - "eptas for max clique on disks and unit balls"
    - "enhanced uplink resource allocation in non orthogonal multiple access systems"
    - "discovering patterns of interest in ip traffic using cliques in bipartite link streams"
    - "delivery time reduction for order constrained applications using binary network codes"
    - "data dissemination using instantly decodable binary codes in fog radio access networks"
    - "on multiaspect graphs"
    - "distributed hybrid scheduling in multi cloud networks using conflict graphs"
    - "resilient backhaul network design using hybrid radio free space optical technology"

Connected through hyperedge HE-2 (induced by source paper "reactive proximity data structures for graphs"):
  with members:
    - "dynamic geometric data structures via shallow cuttings"
    - "better tradeoffs for exact distance oracles in planar graphs"
    - "crossing patterns in nonplanar road networks"
    - "defining equitable geographic districts in road networks via stable matching"
    - "dynamic planar voronoi diagrams for general distance functions and their algorithmic applications"
    - "treetopes and their graphs"
    - "going off road transversal complexity in road networks"
    - "fast hierarchical clustering and other applications of dynamic closest pairs"

Connected through hyperedge HE-3 (induced by source paper "extracting aspects hierarchies using rhetorical structure theory"):
  with members:
    - "method for aspect based sentiment annotation using rhetorical analysis"
    - "a hierarchical model of reviews for aspect based sentiment analysis"
    - "ups and downs modeling the visual evolution of fashion trends with one class collaborative filtering"
    - "two pass discourse segmentation with pairing and global features"

Connected through hyperedge HE-4 (induced by source paper "orienting fully dynamic graphs with worst case time bounds"):
  with members:
    - "simple deterministic algorithms for fully dynamic maximal matching"
    - "a dynamic data structure for counting subgraphs in sparse graphs"
    - "maintaining approximate maximum weighted matching in fully dynamic graphs"
    - "an efficient polynomial time approximation scheme for steiner forest in planar graphs"

Connected through hyperedge HE-5 (induced by source paper "listing all maximal cliques in sparse graphs in near optimal time"):
  with members:
    - "the h index of a graph and its application to dynamic subgraph statistics"
    - "linear time algorithms for finding a dominating set of fixed size in degenerated graphs"
    - "an o m algorithm for cores decomposition of networks"
    - "small maximal independent sets and faster exact graph coloring"

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)