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: "linking imagenet wordnet synsets with wikidata"
  Abstract: The linkage of ImageNet WordNet synsets to Wikidata items will leverage deep learning algorithm with access to a rich multilingual knowledge graph. Here I will describe our on-going efforts in linking the two resources and issues faced in matching the Wikidata and WordNet knowledge graphs. I show an example on how the linkage can be used in a deep learning setting with real-time image classification and labeling in a non-English language and discuss what opportunities lies ahead.

Connected through hyperedge HE-1 (induced by source paper "wikidata from a research perspective a systematic mapping study of wikidata"):
  with members:
    - "using word embeddings for visual data exploration with ontodia and wikidata"
    - "guidelines for systematic mapping studies in security engineering"
    - "wikidata vandalism detection the loganberry vandalism detector at wsdm cup 2017"
    - "overview of the wikidata vandalism detection task at wsdm cup 2017"
    - "learning to generate one sentence biographies from wikidata"
    - "predicting completeness in knowledge bases"
    - "building automated vandalism detection tools for wikidata"
    - "wikidata through the eyes of dbpedia"

Connected through hyperedge HE-2 (induced by source paper "wsd algorithm based on a new method of vector word contexts proximity calculation via epsilon filtration"):
  with members:
    - "calculated attributes of synonym sets"
    - "analysis of wikipedia based corpora for question answering"
    - "texts in meaning out neural language models in semantic similarity task for russian"

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)