human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a review of the characteristics of 108 author level bibliometric indicators"
  Abstract: An increasing demand for bibliometric assessment of individuals has led to a growth of new bibliometric indicators as well as new variants or combinations of established ones. The aim of this review is to contribute with objective facts about the usefulness of bibliometric indicators of the effects of publication activity at the individual level. This paper reviews 108 indicators that can potentially be used to measure performance on individual author-level, and examines the complexity of their calculations in relation to what they are supposed to reflect and ease of end-user application. As such we provide a schematic overview of author-level indicators, where the indicators are broadly categorised into indicators of publication count, indicators that qualify output (on the level of the researcher and journal), indicators of the effect of output (effect as citations, citations normalized to field or the researcher's body of work), indicators that rank the individual's work and indicators of impact over time. Supported by an extensive appendix we present how the indicators are computed, the complexity of the mathematical calculation and demands to data-collection, their advantages and limitations as well as references to surrounding discussion in the bibliometric community. The Appendix supporting this study is available online as supplementary material.

Connected through hyperedge HE-1 (induced by source paper "predicting citation counts based on deep neural network learning techniques"):
  with members:
    - "can scientific impact be predicted"
    - "deep residual learning for image recognition"
    - "very deep convolutional networks for large scale image recognition"
    - "bibliometric indicators of young authors in astrophysics can later stars be predicted"
    - "neural machine translation by jointly learning to align and translate"
    - "will this paper increase your h index scientific impact prediction"
    - "deep visual semantic alignments for generating image descriptions"
    - "learning phrase representations using rnn encoder decoder for statistical machine translation"

Connected through hyperedge HE-2 (induced by source paper "characterisation of the chi χ index and the rec index"):
  with members:
    - "citation indices and dimensional homogeneity"
    - "do pagerank based author rankings outperform simple citation counts"

Connected through hyperedge HE-3 (induced by source paper "author level metrics in the new academic profile platforms the online behaviour of the bibliometrics community"):
  with members:
    - "a novel method for depicting academic disciplines through google scholar citations the case of bibliometrics"
    - "can we use google scholar to identify highly cited documents"
    - "do researchgate scores create ghost academic reputations"
    - "scholars on twitter who and how many are they"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"
    - "do altmetrics point to the broader impact of research an overview of benefits and disadvantages of altmetrics"

Connected through hyperedge HE-4 (induced by source paper "h index and its alternative a review"):
  with members:
    - "restricting the h index to a publication and citation time window a case study of a timed hirsch index"
    - "a variant of the h index to measure recent performance"
    - "impact vitality a measure for excellent scientists"
    - "socializing the h index"
    - "simple arithmetic versus intuitive understanding the case of the impact factor"
    - "central indexes to the citation distribution a complement to the h index"
    - "the inconsistency of the h index"
    - "weighted indices for evaluating the quality of research with multiple authorship"

Connected through hyperedge HE-5 (induced by source paper "nncp a citation count prediction methodology based on deep neural network learning techniques"):
  with members:
    - "deep residual learning for image recognition"
    - "very deep convolutional networks for large scale image recognition"
    - "bibliometric indicators of young authors in astrophysics can later stars be predicted"
    - "deep visual semantic alignments for generating image descriptions"
    - "sequence to sequence learning with neural networks"
    - "speech recognition with deep recurrent neural networks"
    - "how to improve the prediction based on citation impact percentiles for years shortly after the publication date"

Connected through hyperedge HE-6 (induced by source paper "opium in science and society numbers"):
  with members:
    - "core elements in the process of citing publications conceptual overview of the literature"
    - "introducing citedreferencesexplorer crexplorer a program for reference publication year spectroscopy with cited references standardization"
    - "which of the world s institutions employ the most highly cited researchers an analysis of the data from highlycited com"
    - "measuring impact in research evaluations a thorough discussion of methods for effects of and problems with impact measurements"
    - "on the causes of subject specific citation rates in web of science"
    - "research misconduct definitions manifestations and extent"
    - "severe language effect in university rankings particularly germany and france are wronged in citation based rankings"

Connected through hyperedge HE-7 (induced by source paper "judging merits in the age of the h index citizen bibliometrics in biomedicine and economics"):
  with members:
    - "citation analysis may severely underestimate the impact of clinical research as compared to basic research"
    - "are elite journals declining"
    - "the inconsistency of the h index"

Connected through hyperedge HE-8 (induced by source paper "a review of the literature on citation impact indicators"):
  with members:
    - "a sensitivity analysis of researchers productivity rankings to the time of citation observation"
    - "the precision of the arithmetic mean geometric mean and percentiles for citation data an experimental simulation modelling approach"
    - "the journal coverage of web of science and scopus a comparative analysis"
    - "measuring academic influence not all citations are equal"
    - "a review of theory and practice in scientometrics"
    - "comprehensive indicator comparisons intelligible to non experts the case of two snip versions"
    - "methods for estimating the size of google scholar"
    - "large scale analysis of the accuracy of the journal classification systems of web of science and scopus"

Question: Please tell me which class the center node 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)