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 "task assignment on spatial crowdsourcing technical report"):
  Abstract: Recently, with the rapid development of mobile devices and the crowdsourcing platforms, the spatial crowdsourcing has attracted much attention from the database community. Specifically, spatial crowdsourcing refers to sending a location-based request to workers according to their positions, and workers need to physically move to specified locations to conduct tasks. Many works have studied task assignment problems in spatial crowdsourcing, however, their problem definitions are quite different from each other. As a result, there is no work to compare the performances of existing algorithms on task assignment in spatial crowdsourcing. In this paper, we present a comprehensive experimental comparison of most existing algorithms on task assignment in spatial crowdsourcing. Specifically, we first give some general definitions about spatial workers and spatial tasks based on definitions in the existing works studying task assignment problems in spatial crowdsourcing such that the existing algorithms can be applied on same synthetic and real data sets. Then, we provide a uniform implementation for all the algorithms of task assignment problems in spatial crowdsourcing. Finally, based on the results on both synthetic and real data sets, we conclude the strengths and weaknesses of tested algorithms, which can guide further researches on the same area and practical implementations of spatial crowdsourcing systems.

Includes members:
  Member "task assignment on multi skill oriented spatial crowdsourcing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "task allocation in mobile crowd sensing state of the art and future opportunities")
  Member "reliable diversity based spatial crowdsourcing by moving workers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "task allocation in mobile crowd sensing state of the art and future opportunities")

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.DB(Databases)