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: "mining meaning from wikipedia"
  Abstract: Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks. #R##N#This article provides a comprehensive description of this work. It focuses on research that extracts and makes use of the concepts, relations, facts and descriptions found in Wikipedia, and organizes the work into four broad categories: applying Wikipedia to natural language processing; using it to facilitate information retrieval and information extraction; and as a resource for ontology building. The article addresses how Wikipedia is being used as is, how it is being improved and adapted, and how it is being combined with other structures to create entirely new resources. We identify the research groups and individuals involved, and how their work has developed in the last few years. We provide a comprehensive list of the open-source software they have produced.

Connected through hyperedge HE-1 (induced by source paper "alter auxiliary text rewriting tool for natural language generation"):
  with members:
    - "plan write and revise an interactive system for open domain story generation"
    - "evaluating style transfer for text"
    - "what is wrong with style transfer for texts"
    - "delete retrieve generate a simple approach to sentiment and style transfer"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "generating sentences by editing prototypes"
    - "attention is all you need"
    - "adversarially regularized autoencoders"

Connected through hyperedge HE-2 (induced by source paper "semantic search using spreading activation based on ontology"):
  with members:
    - "a generalized vector space model for ontology based information retrieval"
    - "semantic search by latent ontological features"
    - "structural consistency enabling xml keyword search to eliminate spurious results consistently"

Connected through hyperedge HE-3 (induced by source paper "dawt densely annotated wikipedia texts across multiple languages"):
  with members:
    - "high throughput and language agnostic entity disambiguation and linking on user generated data"
    - "global entity ranking across multiple languages"
    - "mining half a billion topical experts across multiple social networks"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"
    - "tagme on the fly annotation of short text fragments by wikipedia entities"

Connected through hyperedge HE-4 (induced by source paper "world literature according to wikipedia introduction to a dbpedia based framework"):
  with members:
    - "cultural anthropology through the lens of wikipedia a comparison of historical leadership networks in the english chinese japanese and german wikipedia"
    - "mining cross cultural relations from wikipedia a study of 31 european food cultures"
    - "bots vs wikipedians anons vs logged ins"
    - "biographical social networks on wikipedia a cross cultural study of links that made history"
    - "the tower of babel meets web 2 0 user generated content and its applications in a multilingual context"

Connected through hyperedge HE-5 (induced by source paper "not at home on the range peer production and the urban rural divide"):
  with members:
    - "it s a man s wikipedia assessing gender inequality in an online encyclopedia"

Connected through hyperedge HE-6 (induced by source paper "exploring semantically related concepts from wikipedia the case of sere"):
  with members:
    - "the google similarity distance"

Connected through hyperedge HE-7 (induced by source paper "simlex 999 evaluating semantic models with genuine similarity estimation"):
  with members:
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"
    - "domain and function a dual space model of semantic relations and compositions"
    - "from frequency to meaning vector space models of semantics"
    - "learning concept hierarchies from text corpora using formal concept analysis"

Connected through hyperedge HE-8 (induced by source paper "thematically reinforced explicit semantic analysis"):
  with members:
    - "a semantic relatedness measure based on combined encyclopedic ontological and collocational knowledge"

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.AI(Artificial Intelligence)