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 "a novel aspect guided deep transition model for aspect based sentiment analysis"):
  Abstract: Aspect based sentiment analysis (ABSA) aims to identify the sentiment polarity towards the given aspect in a sentence, while previous models typically exploit an aspect-independent (weakly associative) encoder for sentence representation generation. In this paper, we propose a novel Aspect-Guided Deep Transition model, named AGDT, which utilizes the given aspect to guide the sentence encoding from scratch with the specially-designed deep transition architecture. Furthermore, an aspect-oriented objective is designed to enforce AGDT to reconstruct the given aspect with the generated sentence representation. In doing so, our AGDT can accurately generate aspect-specific sentence representation, and thus conduct more accurate sentiment predictions. Experimental results on multiple SemEval datasets demonstrate the effectiveness of our proposed approach, which significantly outperforms the best reported results with the same setting.

Includes members:
  Member "context aware embedding for targeted aspect based sentiment analysis":
    also connected through other hyperedges:
      (none)
  Member "utilizing bert for aspect based sentiment analysis via constructing auxiliary sentence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "description based text classification with reinforcement learning")
  Member "open domain targeted sentiment analysis via span based extraction and classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exploiting bert for end to end aspect based sentiment analysis")
  Member "an interactive multi task learning network for end to end aspect based sentiment analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exploiting bert for end to end aspect based sentiment analysis")
  Member "neural aspect and opinion term extraction with mined rules as weak supervision":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "knowing what how and why a near complete solution for aspect based sentiment analysis")
  Member "multi task learning for multi modal emotion recognition and sentiment analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multimodal embeddings from language models")
  Member "doer dual cross shared rnn for aspect term polarity co extraction":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exploiting bert for end to end aspect based sentiment analysis")
  Member "latent variable sentiment grammar":
    also connected through other hyperedges:
      (none)

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)