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: "multi party set reconciliation using characteristic polynomials"
  Abstract: In the standard set reconciliation problem, there are two parties $A_1$ and $A_2$, each respectively holding a set of elements $S_1$ and $S_2$. The goal is for both parties to obtain the union $S_1 \cup S_2$. In many distributed computing settings the sets may be large but the set difference $|S_1-S_2|+|S_2-S_1|$ is small. In these cases one aims to achieve reconciliation efficiently in terms of communication; ideally, the communication should depend on the size of the set difference, and not on the size of the sets. #R##N#Recent work has considered generalizations of the reconciliation problem to multi-party settings, using a framework based on a specific type of linear sketch called an Invertible Bloom Lookup Table. Here, we consider multi-party set reconciliation using the alternative framework of characteristic polynomials, which have previously been used for efficient pairwise set reconciliation protocols, and compare their performance with Invertible Bloom Lookup Tables for these problems.

Connected through hyperedge HE-1 (induced by source paper "bandwidth efficient transaction relay for bitcoin"):
  with members:
    - "dandelion lightweight cryptocurrency networking with formal anonymity guarantees"
    - "txprobe discovering bitcoin s network topology using orphan transactions"
    - "bitcoin ng a scalable blockchain protocol"
    - "deanonymisation of clients in bitcoin p2p network"
    - "bitcoin transaction malleability and mtgox"
    - "majority is not enough bitcoin mining is vulnerable"
    - "simple multi party set reconciliation"
    - "hosting byzantine fault tolerant services on a chord ring"

Connected through hyperedge HE-2 (induced by source paper "reconciling graphs and sets of sets"):
  with members:
    - "models and algorithms for graph watermarking"
    - "graph isomorphism in quasipolynomial time"
    - "tight lower bound on the probability of a binomial exceeding its expectation"
    - "an efficient reconciliation algorithm for social networks"
    - "simple multi party set reconciliation"
    - "invertible bloom lookup tables"
    - "straggler identification in round trip data streams via newton s identities and invertible bloom filters"

Connected through hyperedge HE-3 (induced by source paper "simple multi party set reconciliation"):
  with members:
    - "reconciling similar sets of data"
    - "on thresholds for the appearance of 2 cores in mixed hypergraphs"
    - "randomized algorithms for tracking distributed count frequencies and ranks"
    - "invertible bloom lookup tables"
    - "analyzing network coding gossip made easy"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"
    - "straggler identification in round trip data streams via newton s identities and invertible bloom filters"

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)