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 "evaluating user reputation in online rating systems via an iterative group based ranking method"):
  Abstract: Reputation is a valuable asset in online social lives and it has drawn increased attention. Due to the existence of noisy ratings and spamming attacks, how to evaluate user reputation in online rating systems is especially significant. However, most of the previous ranking-based methods either follow a debatable assumption or have unsatisfied robustness. In this paper, we propose an iterative group-based ranking method by introducing an iterative reputation–allocation process into the original group-based ranking method. More specifically, the reputation of users is calculated based on the weighted sizes of the user rating groups after grouping all users by their rating similarities, and the high reputation users’ ratings have larger weights in dominating the corresponding user rating groups. The reputation of users and the user rating group sizes are iteratively updated until they become stable. Results on two real data sets with artificial spammers suggest that the proposed method has better performance than the state-of-the-art methods and its robustness is considerably improved comparing with the original group-based ranking method. Our work highlights the positive role of considering users’ grouping behaviors towards a better online user reputation evaluation.

Includes members:
  Member "a vertex similarity index for better personalized recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "trapping problem on star type graphs with applications")
  Member "group based ranking method for online rating systems with spamming attacks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a trust based recommendation method using network diffusion processes")
  Member "an iterative method for calculating robust rating scores":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "big data analytics using cloud and crowd")
  Member "towards an objective ranking in online reputation systems the effect of the rating projection":
    also connected through other hyperedges:
      (none)
  Member "a robust ranking algorithm to spamming":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "accumulative time based ranking method to reputation evaluation in information networks")
  Member "the effect of discrete vs continuous valued ratings on reputation and ranking systems":
    also connected through other hyperedges:
      (none)
  Member "iterative filtering for a dynamical reputation system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "group based ranking method for online rating systems with spamming attacks")

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)