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 "measuring the academic reputation through citation networks via pagerank"):
  Abstract: The objective assessment of the prestige of an academic institution is a difficult and hotly debated task. In the last few years, different types of University Rankings have been proposed to quantify the excellence of different research institutions in the world. Albeit met with criticism in some cases, the relevance of university rankings is being increasingly acknowledged: indeed, rankings are having a major impact on the design of research policies, both at the institutional and governmental level. Yet, the debate on what rankings are {\em exactly} measuring is enduring. Here, we address the issue by measuring a quantitive and reliable proxy of the academic reputation of a given institution and by evaluating its correlation with different university rankings. Specifically, we study citation patterns among universities in five different Web of Science Subject Categories and use the \pr~algorithm on the five resulting citation networks. The rationale behind our work is that scientific citations are driven by the reputation of the reference so that the PageRank algorithm is expected to yield a rank which reflects the reputation of an academic institution in a specific field. Our results allow to quantifying the prestige of a set of institutions in a certain research field based only on hard bibliometric data. Given the volume of the data analysed, our findings are statistically robust and less prone to bias, at odds with ad--hoc surveys often employed by ranking bodies in order to attain similar results. Because our findings are found to correlate extremely well with the ARWU Subject rankings, the approach we propose in our paper may open the door to new, Academic Ranking methodologies that go beyond current methods by reconciling the qualitative evaluation of Academic Prestige with its quantitative measurements via publication impact.

Includes members:
  Member "a critical comparative analysis of five world university rankings":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the differing meanings of indicators under different policy contexts the case of internationalisation")
  Member "wikipedia ranking of world universities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "novel version of pagerank cheirank and 2drank for wikipedia in multilingual network using social impact")
  Member "on the causes of subject specific citation rates in web of science":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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 "on the internal dynamics of the shanghai ranking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "world influence and interactions of universities from wikipedia networks")
  Member "the leiden ranking 2011 2012 data collection indicators and interpretation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an evaluation of percentile measures of citation impact and a proposal for making them better")
  Member "pagerank for ranking authors in co citation networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "assigning credit to scientific datasets using article citation networks")
  Member "big macs and eigenfactor scores don t let correlation coefficients fool you":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "systematic analysis of agreement between metrics and peer review in the uk ref")

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)