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: "analysing timelines of national histories across wikipedia editions a comparative computational approach"
  Abstract: Portrayals of history are never complete, and each description inherently exhibits a specific viewpoint and emphasis. In this paper, we aim to automatically identify such differences by computing timelines and detecting temporal focal points of written history across languages on Wikipedia. In particular, we study articles related to the history of all UN member states and compare them in 30 language editions. We develop a computational approach that allows to identify focal points quantitatively, and find that Wikipedia narratives about national histories (i) are skewed towards more recent events (recency bias) and (ii) are distributed unevenly across the continents with significant focus on the history of European countries (Eurocentric bias). We also establish that national historical timelines vary across language editions, although average interlingual consensus is rather high. We hope that this paper provides a starting point for a broader computational analysis of written history on Wikipedia and elsewhere.

Connected through hyperedge HE-1 (induced by source paper "what is trending on wikipedia capturing trends and language biases across wikipedia editions"):
  with members:
    - "a graph structured dataset for wikipedia research"
    - "why the world reads wikipedia beyond english speakers"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "why we read wikipedia"
    - "mining cross cultural relations from wikipedia a study of 31 european food cultures"

Connected through hyperedge HE-2 (induced by source paper "uneven coverage of natural disasters in wikipedia the case of flood"):
  with members:
    - "integrating social media into a pan european flood awareness system a multilingual approach"
    - "not at home on the range peer production and the urban rural divide"
    - "twitter as a lifeline human annotated twitter corpora for nlp of crisis related messages"
    - "disaster monitoring with wikipedia and online social networking sites structured data and linked data fragments to the rescue"

Connected through hyperedge HE-3 (induced by source paper "why the world reads wikipedia beyond english speakers"):
  with members:
    - "why we read wikipedia"
    - "what makes a link successful on wikipedia"
    - "measuring urban deprivation from user generated content"
    - "cultures in community question answering"
    - "you are what you eat and drink identifying cultural boundaries by analyzing food drink habits in foursquare"
    - "detecting memory and structure in human navigation patterns using markov chain models of varying order"
    - "mining cross cultural relations from wikipedia a study of 31 european food cultures"

Connected through hyperedge HE-4 (induced by source paper "query for architecture click through military comparing the roles of search and navigation on wikipedia"):
  with members:
    - "toktrack a complete token provenance and change tracking dataset for the english wikipedia"
    - "why we read wikipedia"
    - "improving website hyperlink structure using server logs"
    - "what makes a link successful on wikipedia"
    - "hyptrails a bayesian approach for comparing hypotheses about human trails on the web"
    - "detecting memory and structure in human navigation patterns using markov chain models of varying order"

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)