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: "accuracy of simple initials based methods for author name disambiguation"
  Abstract: There are a number of solutions that perform unsupervised name disambiguation based on the similarity of bibliographic records or common coauthorship patterns. Whether the use of these advanced methods, which are often difficult to implement, is warranted depends on whether the accuracy of the most basic disambiguation methods, which only use the author's last name and initials, is sufficient for a particular purpose. We derive realistic estimates for the accuracy of simple, initials-based methods using simulated bibliographic datasets in which the true identities of authors are known. Based on the simulations in five diverse disciplines we find that the first initial method already correctly identifies 97% of authors. An alternative simple method, which takes all initials into account, is typically two times less accurate, except in certain datasets that can be identified by applying a simple criterion. Finally, we introduce a new name-based method that combines the features of first initial and all initials methods by implicitly taking into account the last name frequency and the size of the dataset. This hybrid method reduces the fraction of incorrectly identified authors by 10–30% over the first initial method.

Connected through hyperedge HE-1 (induced by source paper "topic modeling the reading and writing behavior of information foragers"):
  with members:
    - "exploration and exploitation of victorian science in darwin s reading notebooks"
    - "multi level computational methods for interdisciplinary research in the hathitrust digital library"
    - "towards evaluation of cultural scale claims in light of topic model sampling effects"
    - "the wisdom of the few supertaggers in collaborative tagging systems"
    - "multilingual topic models for unaligned text"
    - "a family of statistical symmetric divergences based on jensen s inequality"

Connected through hyperedge HE-2 (induced by source paper "predicting publication productivity for researchers a piecewise poisson model"):
  with members:
    - "predicting citation counts based on deep neural network learning techniques"
    - "predicting publication long term impact through a combination of early citations and journal impact factor"
    - "can scientific impact be predicted"
    - "how to improve the prediction based on citation impact percentiles for years shortly after the publication date"

Connected through hyperedge HE-3 (induced by source paper "evaluating author name disambiguation for digital libraries a case of dblp"):
  with members:
    - "homonym detection in curated bibliographies learning from dblp s experience full version"
    - "evaluating co authorship networks in author name disambiguation for common names"
    - "distortive effects of initial based name disambiguation on measurements of large scale coauthorship networks"
    - "ethnicity sensitive author disambiguation using semi supervised learning"
    - "growth rates of modern science a bibliometric analysis based on the number of publications and cited references"
    - "exploiting citation networks for large scale author name disambiguation"
    - "coauthorship and citation patterns in the physical review"
    - "a heuristic approach to author name disambiguation in bibliometrics databases for large scale research assessments"

Connected through hyperedge HE-4 (induced by source paper "interests diffusion on a semantic multiplex"):
  with members:
    - "interests diffusion in social networks"
    - "exploiting citation networks for large scale author name disambiguation"
    - "quantifying long term scientific impact"

Connected through hyperedge HE-5 (induced by source paper "distortive effects of initial based name disambiguation on measurements of large scale coauthorship networks"):
  with members:
    - "coauthorship and citation patterns in the physical review"

Connected through hyperedge HE-6 (induced by source paper "interests diffusion in social networks"):
  with members:
    - "exploiting citation networks for large scale author name disambiguation"
    - "quantifying long term scientific impact"
    - "semantic similarity in a taxonomy an information based measure and its application to problems of ambiguity in natural language"

Connected through hyperedge HE-7 (induced by source paper "topological collaborative approach for disambiguating authors names in collaborative networks"):
  with members:
    - "a systematic comparison of supervised classifiers"

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)