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: "time dependent hierarchical dirichlet model for timeline generation"
  Abstract: Timeline Generation aims at summarizing news from different epochs and telling readers how an event evolves. It is a new challenge that combines salience ranking with novelty detection. For long-term public events, the main topic usually includes various aspects across different epochs and each aspect has its own evolving pattern. Existing approaches neglect such hierarchical topic structure involved in the news corpus in timeline generation. In this paper, we develop a novel time-dependent Hierarchical Dirichlet Model (HDM) for timeline generation. Our model can aptly detect different levels of topic information across corpus and such structure is further used for sentence selection. Based on the topic mined fro HDM, sentences are selected by considering different aspects such as relevance, coherence and coverage. We develop experimental systems to evaluate 8 long-term events that public concern. Performance comparison between different systems demonstrates the effectiveness of our model in terms of ROUGE metrics.

Connected through hyperedge HE-1 (induced by source paper "presenting a new dataset for the timeline generation problem"):
  with members:
    - "timeline a dynamic hierarchical dirichlet process model for recovering birth death and evolution of topics in text stream"

Connected through hyperedge HE-2 (induced by source paper "adaptive representations for tracking breaking news on twitter"):
  with members:
    - "timeline generation tracking individuals on twitter"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

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.CL(Computation and Language)