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: "robust clustering of languages across wikipedia growth"
  Abstract: Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.

Connected through hyperedge HE-1 (induced by source paper "word sense induction using word embeddings and community detection in complex networks"):
  with members:
    - "word sense disambiguation a complex network approach"
    - "text authorship identified using the dynamics of word co occurrence networks"
    - "using network science and text analytics to produce surveys in a scientific topic"
    - "clustering algorithms a comparative approach"
    - "a complex network approach to stylometry"
    - "probing the topological properties of complex networks modeling short written texts"
    - "comparing the topological properties of real and artificially generated scientific manuscripts"
    - "inducing language networks from continuous space word representations"

Connected through hyperedge HE-2 (induced by source paper "world influence and interactions of universities from wikipedia networks"):
  with members:
    - "capturing the influence of geopolitical ties from wikipedia with reduced google matrix"
    - "analysis of world terror networks from the reduced google matrix of wikipedia"
    - "wikiometrics a wikipedia based ranking system"
    - "wikipedia mining of hidden links between political leaders"
    - "wikipedia ranking of world universities"
    - "interactions of cultures and top people of wikipedia from ranking of 24 language editions"
    - "on the internal dynamics of the shanghai ranking"
    - "towards physical laws for software architecture"

Connected through hyperedge HE-3 (induced by source paper "analysis of world terror networks from the reduced google matrix of wikipedia"):
  with members:
    - "multi cultural wikipedia mining of geopolitics interactions leveraging reduced google matrix analysis"
    - "even good bots fight the case of wikipedia"
    - "wikipedia mining of hidden links between political leaders"
    - "wikipedia ranking of world universities"
    - "interactions of cultures and top people of wikipedia from ranking of 24 language editions"

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)