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 "the relation between eigenfactor audience factor and influence weight"):
  Abstract: We present a theoretical and empirical analysis of a number of bibliometric indicators of journal performance. We focus on three indicators in particular, namely the Eigenfactor indicator, the audience factor, and the influence weight indicator. Our main finding is that the last two indicators can be regarded as a kind of special cases of the first indicator. We also find that the three indicators can be nicely characterized in terms of two properties. We refer to these properties as the property of insensitivity to field differences and the property of insensitivity to insignificant journals. The empirical results that we present illustrate our theoretical findings. We also show empirically that the differences between various indicators of journal performance are quite substantial.

Includes members:
  Member "pagerank for ranking authors in co citation networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "assigning credit to scientific datasets using article citation networks")
  Member "measuring contextual citation impact of scientific journals":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "how well does i3 perform for impact measurement compared to other bibliometric indicators the convergent validity of several field normalized indicators")
  Member "a principal component analysis of 39 scientific impact measures":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the relationship between usage and citations in an open access mega journal")
  Member "big macs and eigenfactor scores don t let correlation coefficients fool you":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "systematic analysis of agreement between metrics and peer review in the uk ref")
  Member "the sjr indicator a new indicator of journals scientific prestige":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "individual bibliometric assessment university of vienna from numbers to multidimensional profiles")
  Member "eigenfactor does the principle of repeated improvement result in better journal impact estimates than raw citation counts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a review of the literature on citation impact indicators")

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)