human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "from feature extraction to classification a multidisciplinary approach applied to portuguese granites"
  Abstract: The purpose of this paper is to present a complete methodology based on a multidisciplinary approach, that goes from the extraction of features till the classification of a set of different portuguese granites. The set of tools to extract the features that characterise polished surfaces of the granites is mainly based on mathematical morphology. The classification methodology is based on a genetic algorithm capable of search the input feature space used by the nearest neighbour rule classifier. Results show that is adequate to perform feature reduction and simultaneous improve the recognition rate. Moreover, the present methodology represents a robust strategy to understand the proper nature of the images treated, and their discriminant features. KEYWORDS: Portuguese grey granites, feature extraction, mathematical morphology, feature reduction, genetic algorithms, nearest neighbour rule classifiers (k-NNR).

Connected through hyperedge HE-1 (induced by source paper "swarming around shellfish larvae"):
  with members:
    - "self organized stigmergic document maps environment as a mechanism for context learning"
    - "evolving a stigmergic self organized data mining"
    - "artificial ant colonies in digital image habitats a mass behaviour effect study on pattern recognition"
    - "web usage mining using artificial ant colony clustering and linear genetic programming"
    - "swarms on continuous data"

Connected through hyperedge HE-2 (induced by source paper "antids self organized ant based clustering model for intrusion detection system"):
  with members:
    - "self organized stigmergic document maps environment as a mechanism for context learning"
    - "evolving a stigmergic self organized data mining"
    - "artificial ant colonies in digital image habitats a mass behaviour effect study on pattern recognition"
    - "web usage mining using artificial ant colony clustering and linear genetic programming"
    - "swarms on continuous data"

Connected through hyperedge HE-3 (induced by source paper "swarms on continuous data"):
  with members:
    - "self organized stigmergic document maps environment as a mechanism for context learning"
    - "artificial ant colonies in digital image habitats a mass behaviour effect study on pattern recognition"

Question: Please tell me which class the center node 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.AI(Artificial Intelligence)