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: "stream vbyte faster byte oriented integer compression"
  Abstract: Arrays of integers are often compressed in search engines. Though there are many ways to compress integers, we are interested in the popular byte-oriented integer compression techniques (e.g., VByte or Google's Varint-GB). They are appealing due to their simplicity and engineering convenience. Amazon's varint-G8IU is one of the fastest byte-oriented compression technique published so far. It makes judicious use of the powerful single-instruction-multiple-data (SIMD) instructions available in commodity processors. To surpass varint-G8IU, we present Stream VByte, a novel byte-oriented compression technique that separates the control stream from the encoded data. Like varint-G8IU, Stream VByte is well suited for SIMD instructions. We show that Stream VByte decoding can be up to twice as fast as varint-G8IU decoding over real data sets. In this sense, Stream VByte establishes new speed records for byte-oriented integer compression, at times exceeding the speed of the memcpy function. On a 3.4GHz  Haswell processor, it decodes more than 4 billion  differentially-coded integers per second from RAM to L1 cache.

Connected through hyperedge HE-1 (induced by source paper "techniques for inverted index compression"):
  with members:
    - "on optimally partitioning variable byte codes"
    - "on slicing sorted integer sequences"
    - "roaring bitmaps implementation of an optimized software library"
    - "compressing graphs and indexes with recursive graph bisection"
    - "consistently faster and smaller compressed bitmaps with roaring"
    - "vectorized vbyte decoding"
    - "asymmetric numeral systems entropy coding combining speed of huffman coding with compression rate of arithmetic coding"
    - "quasi succinct indices"

Connected through hyperedge HE-2 (induced by source paper "on slicing sorted integer sequences"):
  with members:
    - "on optimally partitioning variable byte codes"
    - "roaring bitmaps implementation of an optimized software library"
    - "a fast x86 implementation of select"
    - "consistently faster and smaller compressed bitmaps with roaring"
    - "vectorized vbyte decoding"
    - "quasi succinct indices"
    - "decoding billions of integers per second through vectorization"

Connected through hyperedge HE-3 (induced by source paper "variable byte encoding is now space efficient too"):
  with members:
    - "universal indexes for highly repetitive document collections"
    - "vectorized vbyte decoding"
    - "asymmetric numeral systems entropy coding combining speed of huffman coding with compression rate of arithmetic coding"
    - "quasi succinct indices"
    - "decoding billions of integers per second through vectorization"
    - "on optimally partitioning a text to improve its compression"
    - "improving table compression with combinatorial optimization"

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)