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 "looking beyond a clever narrative visual context and attention are primary drivers of affect in video advertisements"):
  Abstract: Emotion evoked by an advertisement plays a key role in influencing brand recall and eventual consumer choices. Automatic ad affect recognition has several useful applications. However, the use of content-based feature representations does not give insights into how affect is modulated by aspects such as the ad scene setting, salient object attributes and their interactions. Neither do such approaches inform us on how humans prioritize visual information for ad understanding. Our work addresses these lacunae by decomposing video content into detected objects, coarse scene structure, object statistics and actively attended objects identified via eye-gaze. We measure the importance of each of these information channels by systematically incorporating related information into ad affect prediction models. Contrary to the popular notion that ad affect hinges on the narrative and the clever use of linguistic and social cues, we find that actively attended objects and the coarse scene structure better encode affective information as compared to individual scene objects or conspicuous background elements.

Includes members:
  Member "multimodal sentiment analysis with word level fusion and reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gated mechanism for attention based multimodal sentiment analysis")
  Member "yolov3 an incremental improvement":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "perception and decision making of autonomous systems in the era of learning an overview")
  Member "an eeg based image annotation system":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "eeg based evaluation of cognitive workload induced by acoustic parameters for data sonification")
  Member "affect recognition in ads with application to computational advertising":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "affective computing for large scale heterogeneous multimedia data a survey")
  Member "evaluating content centric vs user centric ad affect recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "affective computing for large scale heterogeneous multimedia data a survey")
  Member "automatic understanding of image and video advertisements":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recommending themes for ad creative design via visual linguistic representations")
  Member "object detection can be improved using human derived contextual expectations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recognition of advertisement emotions with application to computational advertising")
  Member "pet an eye tracking dataset for animal centric pascal object classes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "predicting goal directed attention control using inverse reinforcement learning")

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.CV(Computer Vision and Pattern Recognition)