human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "topic modeling the reading and writing behavior of information foragers"):
  Abstract: The general problem of "information foraging" in an environment about which agents have incomplete information has been explored in many fields, including cognitive psychology, neuroscience, economics, finance, ecology, and computer science. In all of these areas, the searcher aims to enhance future performance by surveying enough of existing knowledge to orient themselves in the information space. Individuals can be viewed as conducting a cognitive search in which they must balance exploration of ideas that are novel to them against exploitation of knowledge in domains in which they are already expert. #R##N#In this dissertation, I present several case studies that demonstrate how reading and writing behaviors interact to construct personal knowledge bases. These studies use LDA topic modeling to represent the information environment of the texts each author read and wrote. Three studies revolve around Charles Darwin. Darwin left detailed records of every book he read for 23 years, from disembarking from the H.M.S. Beagle to just after publication of The Origin of Species. Additionally, he left copies of his drafts before publication. I characterize his reading behavior, then show how that reading behavior interacted with the drafts and subsequent revisions of The Origin of Species, and expand the dataset to include later readings and writings. Then, through a study of Thomas Jefferson's correspondence, I expand the study to non-book data. Finally, through an examination of neuroscience citation data, I move from individual behavior to collective behavior in constructing an information environment. Together, these studies reveal "the interplay between individual and collective phenomena where innovation takes place" (Tria et al. 2014).

Includes members:
  Member "exploration and exploitation of victorian science in darwin s reading notebooks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how we do things with words analyzing text as social and cultural data")
  Member "multi level computational methods for interdisciplinary research in the hathitrust digital library":
    also connected through other hyperedges:
      (none)
  Member "towards evaluation of cultural scale claims in light of topic model sampling effects":
    also connected through other hyperedges:
      (none)
  Member "the wisdom of the few supertaggers in collaborative tagging systems":
    also connected through other hyperedges:
      (none)
  Member "accuracy of simple initials based methods for author name disambiguation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "predicting publication productivity for researchers a piecewise poisson model")
  Member "multilingual topic models for unaligned text":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a resource free evaluation metric for cross lingual word embeddings based on graph modularity")
  Member "a family of statistical symmetric divergences based on jensen s inequality":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "explain graph neural networks to understand weighted graph features in node classification")

Question: Please tell me which class the source paper 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)