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: "the birth of collective memories analyzing emerging entities in text streams"
  Abstract: We study how collective memories are formed online. We do so by tracking entities that emerge in public discourse, that is, in online text streams such as social media and news streams, before they are incorporated into Wikipedia, which, we argue, can be viewed as an online place for collective memory. By tracking how entities emerge in public discourse, i.e., the temporal patterns between their first mention in online text streams and subsequent incorporation into collective memory, we gain insights into how the collective remembrance process happens online. Specifically, we analyze nearly 80,000 entities as they emerge in online text streams before they are incorporated into Wikipedia. The online text streams we use for our analysis comprise of social media and news streams, and span over 579 million documents in a timespan of 18 months. We discover two main emergence patterns: entities that emerge in a "bursty" fashion, i.e., that appear in public discourse without a precedent, blast into activity and transition into collective memory. Other entities display a "delayed" pattern, where they appear in public discourse, experience a period of inactivity, and then resurface before transitioning into our cultural collective memory.

Connected through hyperedge HE-1 (induced by source paper "novel entity discovery from web tables"):
  with members:
    - "auto completion for data cells in relational tables"
    - "matchzoo a learning practicing and developing system for neural text matching"
    - "end to end neural entity linking"
    - "ad hoc table retrieval using semantic similarity"
    - "improving entity linking by modeling latent relations between mentions"
    - "on the fly table generation"
    - "deep joint entity disambiguation with local neural attention"

Connected through hyperedge HE-2 (induced by source paper "early discovery of emerging entities in microblogs"):
  with members:
    - "design challenges and misconceptions in neural sequence labeling"
    - "neural architectures for named entity recognition"
    - "word storms multiples of word clouds for visual comparison of documents"

Connected through hyperedge HE-3 (induced by source paper "unsupervised context retrieval for long tail entities"):
  with members:
    - "on type aware entity retrieval"
    - "document filtering for long tail entities"

Connected through hyperedge HE-4 (induced by source paper "improved and robust controversy detection in general web pages using semantic approaches under large scale conditions"):
  with members:
    - "adam a method for stochastic optimization"
    - "convolutional neural networks for sentence classification"
    - "neural machine translation by jointly learning to align and translate"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-5 (induced by source paper "sleeping beauties in meme diffusion"):
  with members:
    - "local variation of hashtag spike trains and popularity in twitter"
    - "wikipedia page view reflects web search trend"
    - "who creates trends in online social media the crowd or opinion leaders"
    - "can cascades be predicted"
    - "predicting successful memes using network and community structure"
    - "virality prediction and community structure in social networks"
    - "how to improve the prediction based on citation impact percentiles for years shortly after the publication date"
    - "quantifying long term scientific impact"

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.IR(Information Retrieval)