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: "analysing covert social network foundation behind terrorism disaster"
  Abstract: This paper addresses a method to analyse the covert social network foundation hidden behind the terrorism disaster. It is to solve a node discovery problem, which means to discover a node, which functions relevantly in a social network, but escaped from monitoring on the presence and mutual relationship of nodes. The method aims at integrating the expert investigator's prior understanding, insight on the terrorists' social network nature derived from the complex graph theory and computational data processing. The social network responsible for the 9/11 attack in 2001 is used to execute simulation experiment to evaluate the performance of the method.

Connected through hyperedge HE-1 (induced by source paper "on the computational models for the analysis of illicit activities"):
  with members:
    - "ceai ccm based email authorship identification model"
    - "modeling suspicious email detection using enhanced feature selection"

Connected through hyperedge HE-2 (induced by source paper "discovering network behind infectious disease outbreak"):
  with members:
    - "network inference from co occurrences"
    - "node discovery problem for a social network"

Connected through hyperedge HE-3 (induced by source paper "node discovery in a networked organization"):
  with members:
    - "learning the structure of dynamic probabilistic networks"
    - "reflective visualisation and verbalisation of unconscious preference"
    - "network inference from co occurrences"
    - "search in power law networks"

Connected through hyperedge HE-4 (induced by source paper "intuitive visualization of the intelligence for the run down of terrorist wire pullers"):
  with members:
    - "learning the structure of dynamic probabilistic networks"

Connected through hyperedge HE-5 (induced by source paper "node discovery problem for a social network"):
  with members:
    - "learning the structure of dynamic probabilistic networks"
    - "network inference from co occurrences"
    - "search in power law networks"

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)