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: "bubing massive crawling for the masses"
  Abstract: Although web crawlers have been around for twenty years by now, there is virtually no freely available, opensource crawling software that guarantees high throughput, overcomes the limits of single-machine systems and at the same time scales linearly with the amount of resources available. This paper aims at filling this gap, through the description of BUbiNG, our next-generation web crawler built upon the authors' experience with UbiCrawler [Boldi et al. 2004] and on the last ten years of research on the topic. BUbiNG is an opensource Java fully distributed crawler; a single BUbiNG agent, using sizeable hardware, can crawl several thousands pages per second respecting strict politeness constraints, both host- and IP-based. Unlike existing open-source distributed crawlers that rely on batch techniques (like MapReduce), BUbiNG job distribution is based on modern high-speed protocols so to achieve very high throughput.

Connected through hyperedge HE-1 (induced by source paper "peeling close to the orientability threshold spatial coupling in hashing based data structures"):
  with members:
    - "dense peelable random uniform hypergraphs"
    - "fast scalable construction of minimal perfect hash functions"
    - "the multiple orientability thresholds for random hypergraphs"
    - "on the insertion time of random walk cuckoo hashing"
    - "high speed hashing for integers and strings"
    - "cache oblivious peeling of random hypergraphs"
    - "thresholds of spatially coupled systems via lyapunov s method"
    - "a simple proof of threshold saturation for coupled scalar recursions"

Connected through hyperedge HE-2 (induced by source paper "2ps high quality edge partitioning with two phase streaming"):
  with members:
    - "hype massive hypergraph partitioning with neighborhood expansion"
    - "scalable edge partitioning"
    - "a streaming algorithm for graph clustering"
    - "adwise adaptive window based streaming edge partitioning for high speed graph processing"
    - "defining and evaluating network communities based on ground truth"
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"

Connected through hyperedge HE-3 (induced by source paper "planted hitting set recovery in hypergraphs"):
  with members:
    - "three hypergraph eigenvector centralities"
    - "core fringe link prediction"
    - "simplicial closure and higher order link prediction"
    - "found graph data and planted vertex covers"
    - "social networks under stress"
    - "pagerank beyond the web"
    - "axioms for centrality"

Connected through hyperedge HE-4 (induced by source paper "efficient gauss elimination for near quadratic matrices with one short random block per row with applications"):
  with members:
    - "dense peelable random uniform hypergraphs"
    - "a unified approach to linear probing hashing with buckets"
    - "cache oblivious peeling of random hypergraphs"

Connected through hyperedge HE-5 (induced by source paper "kadabra is an adaptive algorithm for betweenness via random approximation"):
  with members:
    - "dynamic merging of frontiers for accelerating the evaluation of betweenness centrality"
    - "computing top k closeness centrality faster in unweighted graphs"
    - "metropolis hastings algorithms for estimating betweenness centrality in large networks"
    - "an axiomatic and an average case analysis of algorithms and heuristics for metric properties of graphs"
    - "abra approximating betweenness centrality in static and dynamic graphs with rademacher averages"
    - "fully dynamic approximation of betweenness centrality"
    - "networkit an interactive tool suite for high performance network analysis"
    - "into the square on the complexity of quadratic time solvable problems"

Connected through hyperedge HE-6 (induced by source paper "an efficient streaming algorithm for the submodular cover problem"):
  with members:
    - "tight bounds for single pass streaming complexity of the set cover problem"
    - "towards tight bounds for the streaming set cover problem"
    - "incidence geometries and the pass complexity of semi streaming set cover"
    - "analytical approach to parallel repetition"
    - "defining and evaluating network communities based on ground truth"
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"

Connected through hyperedge HE-7 (induced by source paper "fast scalable construction of minimal perfect hash functions"):
  with members:
    - "fast prefix search in little space with applications"
    - "cache oblivious peeling of random hypergraphs"
    - "satisfiability thresholds beyond k xorsat"
    - "sharp load thresholds for cuckoo hashing"
    - "tight thresholds for cuckoo hashing via xorsat"

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.IR(Information Retrieval)