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 "application of the sp theory of intelligence to the understanding of natural vision and the development of computer vision"):
  Abstract: The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.

Includes members:
  Member "big data and the sp theory of intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "introduction to the sp theory of intelligence")
  Member "the sp theory of intelligence benefits and applications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "introduction to the sp theory of intelligence")
  Member "the sp theory of intelligence an overview":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "introduction to the sp theory of intelligence")
  Member "information compression intelligence computing and mathematics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the sp theory of intelligence distinctive features and advantages")
  Member "scene parsing with multiscale feature learning purity trees and optimal covers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the gap between theory and practice in function approximation with deep neural networks")
  Member "towards an intelligent database system founded on the sp theory of computing and cognition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "introduction to the sp theory of intelligence")
  Member "medical diagnosis as pattern recognition in a framework of information compression by multiple alignment unification and search":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "introduction to the sp theory of intelligence")
  Member "unifying computing and cognition the sp theory and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "detection recognition and tracking of moving objects from real time video via sp theory of intelligence and species inspired pso")

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)