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 "user aware folk popularity rank user popularity based tag recommendation that can enhance social popularity"):
  Abstract: In this paper we propose a method that can enhance the social popularity of a post (i.e., the number of views or likes) by recommending appropriate hash tags considering both content popularity and user popularity. A previous approach called FolkPopularityRank (FP-Rank) considered only the relationship among images, tags, and their popularity. However, the popularity of an image/video is strongly affected by who uploaded it. Therefore, we develop an algorithm that can incorporate user popularity and users' tag usage tendency into the FP-Rank algorithm. The experimental results using 60,000 training images with their accompanying tags and 1,000 test data, which were actually uploaded to a real social network service (SNS), show that, in ten days, our proposed algorithm can achieve 1.2 times more views than the FP-Rank algorithm. This technology would be critical to individual users and companies/brands who want to promote themselves in SNSs.

Includes members:
  Member "stacked cross attention for image text matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adversarial ranking attack and defense")
  Member "a multimodal approach to predict social media popularity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "identifying offensive posts and targeted offense from twitter")
  Member "tagging like humans diverse and distinct image annotation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exact adversarial attack to image captioning via structured output learning with latent variables")
  Member "pay attention to virality understanding popularity of social media videos with the attention mechanism":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "intrinsic image popularity assessment")
  Member "modeling popularity in asynchronous social media streams with recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "modeling information cascades with self exciting processes via generalized epidemic models")
  Member "neural collaborative filtering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "advances in collaborative filtering and ranking")
  Member "use of deep learning in modern recommendation system a summary of recent works":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep learning for sequential recommendation algorithms influential factors and evaluations")
  Member "stack captioning coarse to fine learning for image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mutatt visual textual mutual guidance for referring expression comprehension")

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.SI(Social and Information Networks)