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 "constructing situation specific belief networks"):
  Abstract: This paper describes a process for constructing situation-specific belief networks from a knowledge base of network fragments. A situation-specific network is a minimal query complete network constructed from a knowledge base in response to a query for the probability distribution on a set of target variables given evidence and context variables. We present definitions of query completeness and situation-specific networks. We describe conditions on the knowledge base that guarantee query completeness. The relationship of our work to earlier work on KBMC is also discussed.

Includes members:
  Member "pruning bayesian networks for efficient computation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lazy factored inference for functional probabilistic programming")
  Member "a theoretical framework for context sensitive temporal probability model construction with application to plan projection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lower complexity bounds for lifted inference")
  Member "generating bayesian networks from probability logic knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "survey on models and techniques for root cause analysis")
  Member "network fragments representing knowledge for constructing probabilistic models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bard a structured technique for group elicitation of bayesian networks to support analytic reasoning")
  Member "d separation from theorems to algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "query the model precomputations for efficient inference with bayesian networks")
  Member "integrating model construction and evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reasoning about the value of decision model refinement methods and application")
  Member "tradeoffs in constructing and evaluating temporal influence diagrams":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "tractable inference for complex stochastic processes")
  Member "computational advantages of relevance reasoning in bayesian belief networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "hypothesis management in situation specific network construction")

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.AI(Artificial Intelligence)