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 "measuring similarity between brands using followers post in social media"):
  Abstract: In this paper, we propose a new measure to estimate the similarity between brands via posts of brands' followers on social network services (SNS). Our method was developed with the intention of exploring the brands that customers are likely to jointly purchase. Nowadays, brands use social media for targeted advertising because influencing users' preferences can greatly affect the trends in sales. We assume that data on SNS allows us to make quantitative comparisons between brands. Our proposed algorithm analyzes the daily photos and hashtags posted by each brand's followers. By clustering them and converting them to histograms, we can calculate the similarity between brands. We evaluated our proposed algorithm with purchase logs, credit card information, and answers to the questionnaires. The experimental results show that the purchase data maintained by a mall or a credit card company can predict the co-purchase very well, but not the customer's willingness to buy products of new brands. On the other hand, our method can predict the users' interest on brands with a correlation value over 0.53, which is pretty high considering that such interest to brands are high subjective and individual dependent.

Includes members:
  Member "relational collaborative filtering modeling multiple item relations for recommendation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on knowledge graph based recommender systems")
  Member "billion scale commodity embedding for e commerce recommendation in alibaba":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey of adversarial learning on graphs")
  Member "what your facebook profile picture reveals about your personality":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "what twitter profile and posted images reveal about depression and anxiety")
  Member "learning the latent look unsupervised discovery of a style coherent embedding from fashion images":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "regularizing reasons for outfit evaluation with gradient penalty")
  Member "tag prediction at flickr a view from the darkroom":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mentornet learning data driven curriculum for very deep neural networks on corrupted labels")
  Member "item2vec neural item embedding for collaborative filtering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "attentive item2vec neural attentive user representations")
  Member "emoji2vec learning emoji representations from their description":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "related tasks can share a multi task framework for affective language")
  Member "enriching word vectors with subword information":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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)