human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "production ranking systems a review"):
  Abstract: The problem of ranking is a multi-billion dollar problem. In this paper we present an overview of several production quality ranking systems. We show that due to conflicting goals of employing the most effective machine learning models and responding to users in real time, ranking systems have evolved into a system of systems, where each subsystem can be viewed as a component layer. We view these layers as being data processing, representation learning, candidate selection and online inference. Each layer employs different algorithms and tools, with every end-to-end ranking system spanning multiple architectures. Our goal is to familiarize the general audience with a working knowledge of ranking at scale, the tools and algorithms employed and the challenges introduced by adopting a layered approach.

Includes members:
  Member "beyond keywords and relevance a personalized ad retrieval framework in e commerce sponsored search":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "aiads automated and intelligent advertising system for sponsored search")
  Member "practical constrained optimization of auction mechanisms in e commerce sponsored search advertising":
    also connected through other hyperedges:
      (none)
  Member "eenmf an end to end neural matching framework for e commerce sponsored search":
    also connected through other hyperedges:
      (none)
  Member "deep learning inference in facebook data centers characterization performance optimizations and hardware implications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improving efficiency in neural network accelerator using operands hamming distance optimization")
  Member "billion scale commodity embedding for e commerce recommendation in alibaba":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey of adversarial learning on graphs")
  Member "ann benchmarks a benchmarking tool for approximate nearest neighbor algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximating spectral clustering via sampling a review")
  Member "visually aware fashion recommendation and design with generative image models":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning diverse fashion collocation by neural graph filtering")
  Member "pixie a system for recommending 3 billion items to 200 million users in real time":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "prince provider side interpretability with counterfactual explanations in recommender systems")

Question: Please tell me which class the source paper 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)