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: "fast and compact planar embeddings"
  Abstract: There are many representations of planar graphs, but few are as elegant as Tur\'an's (1984): it is simple and practical, uses only 4 bits per edge, can handle self-loops and multi-edges, and can store any specified embedding. Its main disadvantage has been that "it does not allow efficient searching" (Jacobson, 1989). In this paper we show how to add a sublinear number of bits to Tur\'an's representation such that it supports fast navigation while retaining simplicity. As a consequence of the inherited simplicity, we offer the first efficient parallel construction of a compact encoding of a planar graph embedding. Our experimental results show that the resulting representation uses about 6 bits per edge in practice, supports basic navigation operations within a few microseconds, and can be built sequentially at a rate below 1 microsecond per edge, featuring a linear speedup with a parallel efficiency around 50\% for large datasets.

Connected through hyperedge HE-1 (induced by source paper "indexing graph search trees and applications"):
  with members:
    - "succinct data structures for families of interval graphs"
    - "improved space efficient linear time algorithms for some classical graph problems"
    - "biconnectivity st numbering and other applications of dfs using o n bits"
    - "space efficient biconnected components and recognition of outerplanar graphs"
    - "succinct representations of permutations and functions"

Connected through hyperedge HE-2 (induced by source paper "implementing the topological model succinctly"):
  with members:
    - "fast set intersection and two patterns matching"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-3 (induced by source paper "survey and taxonomy of lossless graph compression and space efficient graph representations"):
  with members:
    - "grammar based graph compression"
    - "compressing networks with super nodes"
    - "graphzip dictionary based compression for mining graph streams"
    - "parallel construction of compact planar embeddings"
    - "compressed representation of dynamic binary relations with applications"
    - "a succinct data structure for self indexing ternary relations"
    - "fully dynamic de bruijn graphs"
    - "compressing graphs and indexes with recursive graph bisection"

Connected through hyperedge HE-4 (induced by source paper "about birds project bioinformatics and information retrieval data structures analysis and design"):
  with members:
    - "compact representations of event sequences"
    - "parallel construction of wavelet trees on multicore architectures"
    - "run compressed rank select for large alphabets"
    - "efficient compression and indexing of trajectories"
    - "grammar compressed sequences with rank select support"
    - "compressed representation of dynamic binary relations with applications"
    - "a succinct data structure for self indexing ternary relations"
    - "aggregated 2d range queries on clustered points"

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)