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: "parallel construction of wavelet trees on multicore architectures"
  Abstract: The wavelet tree has become a very useful data structure to efficiently represent and query large volumes of data in many different domains, from bioinformatics to geographic information systems. One problem with wavelet trees is their construction time. In this paper, we introduce two algorithms that reduce the time complexity of a wavelet tree's construction by taking advantage of nowadays ubiquitous multicore machines. Our first algorithm constructs all the levels of the wavelet in parallel with O(n) time and $$O(n\lg \sigma + \sigma \lg n)$$O(nlgź+źlgn) bits of working space, where n is the size of the input sequence and $$\sigma $$ź is the size of the alphabet. Our second algorithm constructs the wavelet tree in a domain decomposition fashion, using our first algorithm in each segment, reaching $$O(\lg n)$$O(lgn) time and $$O(n\lg \sigma + p\sigma \lg n/\lg \sigma )$$O(nlgź+pźlgn/lgź) bits of extra space, where p is the number of available cores. Both algorithms are practical and report good speedup for large real datasets.

Connected through hyperedge HE-1 (induced by source paper "about birds project bioinformatics and information retrieval data structures analysis and design"):
  with members:
    - "compact representations of event sequences"
    - "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"
    - "navigational rule derivation an algorithm to determine the effect of traffic signs on road networks"

Connected through hyperedge HE-2 (induced by source paper "improved parallel construction of wavelet trees and rank select structures"):
  with members:
    - "simple fast and lightweight parallel wavelet tree construction"
    - "parallel wavelet tree construction"
    - "wavelet trees meet suffix trees"

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)