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: "on randomized algorithms for matching in the online preemptive model"
  Abstract: We investigate the power of randomized algorithms for the maximum cardinality matching (MCM) and the maximum weight matching (MWM) problems in the online preemptive model. In this model, the edges of a graph are revealed one by one and the algorithm is required to always maintain a valid matching. On seeing an edge, the algorithm has to either accept or reject the edge. If accepted, then the adjacent edges are discarded. The complexity of the problem is settled for deterministic algorithms. #R##N#Almost nothing is known for randomized algorithms. A lower bound of $1.693$ is known for MCM with a trivial upper bound of $2$. An upper bound of $5.356$ is known for MWM. We initiate a systematic study of the same in this paper with an aim to isolate and understand the difficulty. We begin with a primal-dual analysis of the deterministic algorithm due to McGregor. All deterministic lower bounds are on instances which are trees at every step. For this class of (unweighted) graphs we present a randomized algorithm which is $\frac{28}{15}$-competitive. The analysis is a considerable extension of the (simple) primal-dual analysis for the deterministic case. The key new technique is that the distribution of primal charge to dual variables depends on the "neighborhood" and needs to be done after having seen the entire input. The assignment is asymmetric: in that edges may assign different charges to the two end-points. Also the proof depends on a non-trivial structural statement on the performance of the algorithm on the input tree. #R##N#The other main result of this paper is an extension of the deterministic lower bound of Varadaraja to a natural class of randomized algorithms which decide whether to accept a new edge or not using independent random choices.

Connected through hyperedge HE-1 (induced by source paper "prophet inequality for bipartite matching merits of being simple and non adaptive"):
  with members:
    - "near optimal online algorithms and fast approximation algorithms for resource allocation problems"
    - "tight competitive ratios of classic matching algorithms in the fully online model"
    - "how to match when all vertices arrive online"
    - "maximizing efficiency in dynamic matching markets"
    - "makespan minimization via posted prices"
    - "prophet inequalities made easy stochastic optimization by pricing non stochastic inputs"
    - "beyond matroids secretary problem and prophet inequality with general constraints"
    - "online contention resolution schemes"

Connected through hyperedge HE-2 (induced by source paper "online matching with general arrivals"):
  with members:
    - "tight bounds for online edge coloring"
    - "tight competitive ratios of classic matching algorithms in the fully online model"
    - "how to match when all vertices arrive online"
    - "online vertex weighted bipartite matching beating 1 1 e with random arrivals"
    - "an economic based analysis of ranking for online bipartite matching"
    - "tighter bounds for online bipartite matching"
    - "online lower bounds via duality"
    - "maximum matching on trees in the online preemptive and the incremental dynamic graph models"

Connected through hyperedge HE-3 (induced by source paper "how to match when all vertices arrive online"):
  with members:
    - "ranking on arbitrary graphs rematch via continuous lp with monotone and boundary condition constraints"
    - "improved bounds for online preemptive matching"
    - "buyback problem approximate matroid intersection with cancellation costs"
    - "online vertex weighted bipartite matching and single bid budgeted allocations"

Connected through hyperedge HE-4 (induced by source paper "preemptive online partitioning of sequences"):
  with members:
    - "improved bounds for online preemptive matching"

Connected through hyperedge HE-5 (induced by source paper "maximum matching on trees in the online preemptive and the incremental dynamic graph models"):
  with members:
    - "fully dynamic approximate maximum matching and minimum vertex cover in o log 3 n worst case update time"
    - "fully dynamic maximal matching in constant update time"
    - "fully dynamic 1 epsilon approximate matchings"
    - "improved bounds for online preemptive matching"
    - "improved approximation guarantees for weighted matching in the semi streaming model"
    - "buyback problem approximate matroid intersection with cancellation costs"

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)