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 "predicting drug responses by propagating interactions through text enhanced drug gene networks"):
  Abstract: Personalized drug response has received public awareness in recent years. How to combine gene test result and drug sensitivity records is regarded as essential in the real-world implementation. Research articles are good sources to train machine predicting, inference, reasoning, etc. In this project, we combine the patterns mined from biological research articles and categorical data to construct a drug-gene interaction network. Then we use the cell line experimental records on gene and drug sensitivity to estimate the edge embeddings in the network. Our model provides white-box explainable predictions of drug response based on gene records, which achieves 94.74% accuracy in binary drug sensitivity prediction task.

Includes members:
  Member "metapad meta pattern discovery from massive text corpora":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "taxoexpan self supervised taxonomy expansion with position enhanced graph neural network")
  Member "automated phrase mining from massive text corpora":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cube2net efficient query specific network construction with data cube organization")
  Member "meta path guided embedding for similarity search in large scale heterogeneous information networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "magnn metapath aggregated graph neural network for heterogeneous graph embedding")
  Member "image captioning with semantic attention":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "aitpr attribute interaction tensor product representation for image caption")
  Member "self critical sequence training for image captioning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "aitpr attribute interaction tensor product representation for image caption")
  Member "a critical review of recurrent neural networks for sequence learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "language models for image captioning the quirks and what works":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "aitpr attribute interaction tensor product representation for image caption")
  Member "effective approaches to attention based neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "attention over parameters for dialogue systems")

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)