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 "quality control in crowdsourcing a survey of quality attributes assessment techniques and assurance actions"):
  Abstract: Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large groups of individuals toward solving problems. Common problems approached with crowdsourcing are labeling images, translating or transcribing text, providing opinions or ideas, and similar—all tasks that computers are not good at or where they may even fail altogether. The introduction of humans into computations and/or everyday work, however, also poses critical, novel challenges in terms of quality control, as the crowd is typically composed of people with unknown and very diverse abilities, skills, interests, personal objectives, and technological resources. This survey studies quality in the context of crowdsourcing along several dimensions, so as to define and characterize it and to understand the current state of the art. Specifically, this survey derives a quality model for crowdsourcing tasks, identifies the methods and techniques that can be used to assess the attributes of the model, and the actions and strategies that help prevent and mitigate quality problems. An analysis of how these features are supported by the state of the art further identifies open issues and informs an outlook on hot future research directions.

Includes members:
  Member "crowd guilds worker led reputation and feedback on crowdsourcing platforms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "crowd coach peer coaching for crowd workers skill growth")
  Member "a glimpse far into the future understanding long term crowd worker quality":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hype a benchmark for human eye perceptual evaluation of generative models")
  Member "optimality of belief propagation for crowdsourced classification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "crowdsourced classification with xor queries fundamental limits and an efficient algorithm")
  Member "embracing error to enable rapid crowdsourcing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "simple and effective regularization methods for training on noisily labeled data with generalization guarantee")
  Member "crowd access path optimization diversity matters":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "combining crowd and machines for multi predicate item screening")
  Member "incentivizing high quality crowdwork":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "crowdsourcing the perception of machine teaching")
  Member "quizz targeted crowdsourcing with a billion potential users":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the goal gradient hypothesis in stack overflow")
  Member "how many workers to ask adaptive exploration for collecting high quality labels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "practice of efficient data collection via crowdsourcing at large scale")

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.HC(Human-Computer Interaction)