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: "biff bloom filter codes fast error correction for large data sets"
  Abstract: Large data sets are increasingly common in cloud and virtualized environments. For example, transfers of multiple gigabytes are commonplace, as are replicated blocks of such sizes. There is a need for fast error-correction or data reconciliation in such settings even when the expected number of errors is small. #R##N#Motivated by such cloud reconciliation problems, we consider error-correction schemes designed for large data, after explaining why previous approaches appear unsuitable. We introduce Biff codes, which are based on Bloom filters and are designed for large data. For Biff codes with a message of length $L$ and $E$ errors, the encoding time is $O(L)$, decoding time is $O(L + E)$ and the space overhead is $O(E)$. Biff codes are low-density parity-check codes; they are similar to Tornado codes, but are designed for errors instead of erasures. Further, Biff codes are designed to be very simple, removing any explicit graph structures and based entirely on hash tables. We derive Biff codes by a simple reduction from a set reconciliation algorithm for a recently developed data structure, invertible Bloom lookup tables. While the underlying theory is extremely simple, what makes this code especially attractive is the ease with which it can be implemented and the speed of decoding. We present results from a prototype implementation that decodes messages of 1 million words with thousands of errors in well under a second.

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"
    - "bubing massive crawling for the masses"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "dense peelable random uniform hypergraphs"):
  with members:
    - "fast scalable construction of minimal perfect hash functions"
    - "the multiple orientability thresholds for random hypergraphs"
    - "cache oblivious peeling of random hypergraphs"
    - "invertible bloom lookup tables"
    - "sharp load thresholds for cuckoo hashing"
    - "bloomier filters a second look"
    - "straggler identification in round trip data streams via newton s identities and invertible bloom filters"

Connected through hyperedge HE-3 (induced by source paper "two party function computation on the reconciled data"):
  with members:
    - "invertible bloom lookup tables"

Connected through hyperedge HE-4 (induced by source paper "optimal las vegas reduction from one way set reconciliation to error correction"):
  with members:
    - "invertible bloom lookup tables"

Connected through hyperedge HE-5 (induced by source paper "hashing for statistics over k partitions"):
  with members:
    - "from independence to expansion and back again"
    - "beyond locality sensitive hashing"
    - "all distances sketches revisited hip estimators for massive graphs analysis"
    - "bottom k and priority sampling set similarity and subset sums with minimal independence"
    - "simple tabulation fast expanders double tabulation and high independence"
    - "on the k independence required by linear probing and minwise independence"
    - "invertible bloom lookup tables"
    - "hyperanf approximating the neighbourhood function of very large graphs on a budget"

Connected through hyperedge HE-6 (induced by source paper "hardness of peeling with stashes"):
  with members:
    - "invertible bloom lookup tables"
    - "tight thresholds for cuckoo hashing via xorsat"
    - "straggler identification in round trip data streams via newton s identities and invertible bloom filters"

Connected through hyperedge HE-7 (induced by source paper "cache oblivious peeling of random hypergraphs"):
  with members:
    - "fast prefix search in little space with applications"
    - "parallel peeling algorithms"
    - "invertible bloom lookup tables"
    - "tight thresholds for cuckoo hashing via xorsat"
    - "bloomier filters a second look"

Connected through hyperedge HE-8 (induced by source paper "parallel peeling algorithms"):
  with members:
    - "the solution space geometry of random linear equations"
    - "invertible bloom lookup tables"
    - "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.DS(Data Structures and Algorithms)