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 set intersection in memory"
  Abstract: Set intersection is a fundamental operation in information retrieval and database systems. This paper introduces linear space data structures to represent sets such that their intersection can be computed in a worst-case efficient way. In general, given k (preprocessed) sets, with totally n elements, we will show how to compute their intersection in expected time O(n/sqrt(w)+kr), where r is the intersection size and w is the number of bits in a machine-word. In addition,we introduce a very simple version of this algorithm that has weaker asymptotic guarantees but performs even better in practice; both algorithms outperform the state of the art techniques in terms of execution time for both synthetic and real data sets and workloads.

Connected through hyperedge HE-1 (induced by source paper "pam parallel augmented maps"):
  with members:
    - "range queries in non blocking k ary search trees"
    - "a general technique for non blocking trees"
    - "fast parallel operations on search trees"

Connected through hyperedge HE-2 (induced by source paper "answering spatial multiple set intersection queries using 2 3 cuckoo hash filters"):
  with members:
    - "cuckoo filter simplification and analysis"
    - "the input output complexity of triangle enumeration"
    - "dynamic set intersection"
    - "thresholds for extreme orientability"
    - "a new data layout for set intersection on gpus"
    - "privacy preserving access of outsourced data via oblivious ram simulation"
    - "fast evaluation of union intersection expressions"

Connected through hyperedge HE-3 (induced by source paper "strongly universal string hashing is fast"):
  with members:
    - "explicit and efficient hash families suffice for cuckoo hashing with a stash"
    - "recursive n gram hashing is pairwise independent at best"
    - "the power of simple tabulation hashing"

Connected through hyperedge HE-4 (induced by source paper "simd compression and the intersection of sorted integers"):
  with members:
    - "quasi succinct indices"
    - "decoding billions of integers per second through vectorization"

Connected through hyperedge HE-5 (induced by source paper "fast marching tree a fast marching sampling based method for optimal motion planning in many dimensions"):
  with members:
    - "asymptotically optimal motion planning using lower bounds on cost"
    - "shortest paths in intersection graphs of unit disks"
    - "julia a fast dynamic language for technical computing"
    - "sampling based algorithms for optimal motion planning"

Connected through hyperedge HE-6 (induced by source paper "decoding billions of integers per second through vectorization"):
  with members:
    - "quasi succinct indices"
    - "processing a trillion cells per mouse click"
    - "reordering columns for smaller indexes"

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.DB(Databases)