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 "c 3 index a pagerank based multi faceted metric for authors performance measurement"):
  Abstract: Ranking scientific authors is an important but challenging task, mostly due to the dynamic nature of the evolving scientific publications. The basic indicators of an author's productivity and impact are still the number of publications and the citation count (leading to the popular metrics such as h-index, g-index etc.). H-index and its popular variants are mostly effective in ranking highly-cited authors, thus fail to resolve ties while ranking medium-cited and low-cited authors who are majority in number. Therefore, these metrics are inefficient to predict the ability of promising young researchers at the beginning of their career. In this paper, we propose $C^3$-index that combines the effect of citations and collaborations of an author in a systematic way using a weighted multi-layered network to rank authors. We conduct our experiments on a massive publication dataset of Computer Science and show that - (i) $C^3$-index is consistent over time, which is one of the fundamental characteristics of a ranking metric, (ii) $C^3$-index is as efficient as h-index and its variants to rank highly-cited authors, (iii) $C^3$-index can act as a conflict resolution metric to break ties in the ranking of medium-cited and low-cited authors, (iv) $C^3$-index can also be used to predict future achievers at the early stage of their career.

Includes members:
  Member "on the discovery of success trajectories of authors":
    also connected through other hyperedges:
      (none)
  Member "do pagerank based author rankings outperform simple citation counts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "characterisation of the chi χ index and the rec index")
  Member "applying weighted pagerank to author citation networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "assigning credit to scientific datasets using article citation networks")
  Member "are researchers that collaborate more at the international level top performers an investigation on the italian university system":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gender disparities in international research collaboration a large scale bibliometric study of 25 000 university professors")
  Member "the inconsistency of the h index":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the h index for research assessment simple and popular but shown by mathematical analysis to be inconsistent and misleading")
  Member "pagerank for ranking authors in co citation networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "assigning credit to scientific datasets using article citation networks")
  Member "applying centrality measures to impact analysis a coauthorship network analysis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "machine learning in network centrality measures tutorial and outlook")
  Member "popular and or prestigious measures of scholarly esteem":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "direct citations between citing publications")

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.DL(Digital Libraries)