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: "towards better understanding researcher strategies in cross lingual event analytics"
  Abstract: With an increasing amount of information on globally important events, there is a growing demand for efficient analytics of multilingual event-centric information. Such analytics is particularly challenging due to the large amount of content, the event dynamics and the language barrier. Although memory institutions increasingly collect event-centric Web content in different languages, very little is known about the strategies of researchers who conduct analytics of such content. In this paper we present researchers’ strategies for the content, method and feature selection in the context of cross-lingual event-centric analytics observed in two case studies on multilingual Wikipedia. We discuss the influence factors for these strategies, the findings enabled by the adopted methods along with the current limitations and provide recommendations for services supporting researchers in cross-lingual event-centric analytics.

Connected through hyperedge HE-1 (induced by source paper "eventkg the hub of event knowledge on the web and biographical timeline generation"):
  with members:
    - "eventkg tl creating cross lingual timelines from an event centric knowledge graph"
    - "eventkg a multilingual event centric temporal knowledge graph"
    - "multiwiki interlingual text passage alignment in wikipedia"
    - "ongoing events in wikipedia a cross lingual case study"
    - "learning to generate one sentence biographies from wikidata"
    - "neural text generation from structured data with application to the biography domain"
    - "history by diversity helping historians search news archives"
    - "timemachine timeline generation for knowledge base entities"

Connected through hyperedge HE-2 (induced by source paper "happening happen predict infer event series completion in a knowledge graph"):
  with members:
    - "eventkg the hub of event knowledge on the web and biographical timeline generation"
    - "inferring missing categorical information in noisy and sparse web markup"
    - "eventkg tl creating cross lingual timelines from an event centric knowledge graph"
    - "eventkg a multilingual event centric temporal knowledge graph"
    - "stranse a novel embedding model of entities and relationships in knowledge bases"
    - "proje embedding projection for knowledge graph completion"
    - "there is no deadline time evolution of wikipedia discussions"

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)