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: "an optimization framework for online ride sharing markets"
  Abstract: Taxi services and product delivery services are instrumental for our modern society. Thanks to the emergence of sharing economy, ride-sharing services such as Uber, Didi, Lyft and Google's Waze Rider are becoming more ubiquitous and grow into an integral part of our everyday lives. However, the efficiency of these services are severely limited by the sub-optimal and imbalanced matching between the supply and demand. We need a generalized framework and corresponding efficient algorithms to address the efficient matching, and hence optimize the performance of these markets. Existing studies for taxi and delivery services are only applicable in scenarios of the one-sided market. In contrast, this work investigates a highly generalized model for the taxi and delivery services in the market economy (abbreviated as"taxi and delivery market") that can be widely used in two-sided markets. Further, we present efficient online and offline algorithms for different applications. We verify our algorithm with theoretical analysis and trace-driven simulations under realistic settings.

Connected through hyperedge HE-1 (induced by source paper "mix and match markov chains mixing times for matching in rideshare"):
  with members:
    - "minimizing latency in online ride and delivery services"
    - "spatio temporal pricing for ridesharing platforms"
    - "efficient large scale fleet management via multi agent deep reinforcement learning"
    - "deep reinforcement learning an overview"
    - "allocation problems in ride sharing platforms online matching with offline reusable resources"
    - "pricing and optimization in shared vehicle systems an approximation framework"
    - "rapidly mixing markov chains a comparison of techniques a survey"

Connected through hyperedge HE-2 (induced by source paper "a probabilistic approach for demand aware ride sharing optimization"):
  with members:
    - "deeppool distributed model free algorithm for ride sharing using deep reinforcement learning"
    - "movi a model free approach to dynamic fleet management"
    - "osmnx new methods for acquiring constructing analyzing and visualizing complex street networks"
    - "predictive positioning and quality of service ridesharing for campus mobility on demand systems"
    - "adaptive caching networks with optimality guarantees"
    - "optimal geographic caching in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "on the real time vehicle placement problem"):
  with members:
    - "space time graph modeling of ride requests based on real world data"
    - "follow the leader if you can hedge if you must"

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.SI(Social and Information Networks)