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 "constraint based inference in probabilistic logic programs"):
  Abstract: Probabilistic Logic Programs (PLPs) generalize traditional logic programs and allow the encoding of models combining logical structure and uncertainty. In PLP, inference is performed by summarizing the possible worlds which entail the query in a suitable data structure, and using it to compute the answer probability. Systems such as ProbLog, PITA, etc., use propositional data structures like explanation graphs, BDDs, SDDs, etc., to represent the possible worlds. While this approach saves inference time due to substructure sharing, there are a number of problems where a more compact data structure is possible. We propose a data structure called Ordered Symbolic Derivation Diagram (OSDD) which captures the possible worlds by means of constraint formulas. We describe a program transformation technique to construct OSDDs via query evaluation, and give procedures to perform exact and approximate inference over OSDDs. Our approach has two key properties. Firstly, the exact inference procedure is a generalization of traditional inference, and results in speedup over the latter in certain settings. Secondly, the approximate technique is a generalization of likelihood weighting in Bayesian Networks, and allows us to perform sampling-based inference with lower rejection rate and variance. We evaluate the effectiveness of the proposed techniques through experiments on several problems. This paper is under consideration for acceptance in TPLP.

Includes members:
  Member "inference in probabilistic logic programs using lifted explanations":
    also connected through other hyperedges:
      (none)
  Member "new liftable classes for first order probabilistic inference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "weighted model counting beyond two variable logic")
  Member "lifted variable elimination for probabilistic logic programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fusing first order knowledge compilation and the lifted junction tree algorithm")
  Member "weighing and integrating evidence for stochastic simulation in bayesian networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gaussian mixture reduction for time constrained approximate inference in hybrid bayesian networks")
  Member "stochastic logic programs sampling inference and applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "adaptive mcmc based inference in probabilistic logic programs")
  Member "simulation approaches to general probabilistic inference on belief networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "survey on models and techniques for root cause analysis")
  Member "clp bn constraint logic programming for probabilistic knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "probabilistic logic neural networks for reasoning")
  Member "the pita system tabling and answer subsumption for reasoning under uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "value of information in probabilistic logic programs")

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.LO(Logic in Computer Science)