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: "well definedness and efficient inference for probabilistic logic programming under the distribution semantics"
  Abstract: The distribution semantics is one of the most prominent approaches for the combination of logic programming and probability theory. Many languages follow this semantics, such as Independent Choice Logic, PRISM, pD, Logic Programs with Annotated Disjunctions (LPADs) and ProbLog. When a program contains functions symbols, the distribution semantics is well-defined only if the set of explanations for a query is finite and so is each explanation. Well-definedness is usually either explicitly imposed or is achieved by severely limiting the class of allowed programs. In this paper we identify a larger class of programs for which the semantics is well-defined together with an efficient procedure for computing the probability of queries. Since LPADs offer the most general syntax, we present our results for them, but our results are applicable to all languages under the distribution semantics. We present the algorithm "Probabilistic Inference with Tabling and Answer subsumption" (PITA) that computes the probability of queries by transforming a probabilistic program into a normal program and then applying SLG resolution with answer subsumption. PITA has been implemented in XSB and tested on six domains: two with function symbols and four without. The execution times are compared with those of ProbLog, cplint and CVE, PITA was almost always able to solve larger problems in a shorter time, on domains with and without function symbols.

Connected through hyperedge HE-1 (induced by source paper "using swish to realise interactive web based tutorials for logic based languages"):
  with members:
    - "programming in logic without logic programming"
    - "inference and learning in probabilistic logic programs using weighted boolean formulas"
    - "structure learning of probabilistic logic programs by searching the clause space"
    - "pengines web logic programming made easy"
    - "swi prolog and the web"
    - "pldoc wiki style literate programming for prolog"
    - "extending classical logic with inductive definitions"

Connected through hyperedge HE-2 (induced by source paper "using linear constraints for logic program termination analysis"):
  with members:
    - "checking termination of bottom up evaluation of logic programs with function symbols"
    - "non termination analysis of logic programs with integer arithmetics"
    - "disjunctive asp with functions decidable queries and effective computation"
    - "automated termination analysis for logic programs with cut"
    - "automated termination proofs for logic programs by term rewriting"
    - "on termination of meta programs"
    - "termination proofs for logic programs with tabling"

Connected through hyperedge HE-3 (induced by source paper "structure learning of probabilistic logic programs by searching the clause space"):
  with members:
    - "the bayesian structural em algorithm"
    - "clp bn constraint logic programming for probabilistic knowledge"
    - "unachievable region in precision recall space and its effect on empirical evaluation"
    - "the pita system tabling and answer subsumption for reasoning under uncertainty"
    - "on the implementation of the probabilistic logic programming language problog"
    - "cp logic a language of causal probabilistic events and its relation to logic programming"
    - "parameter learning of logic programs for symbolic statistical modeling"

Connected through hyperedge HE-4 (induced by source paper "inference and learning in probabilistic logic programs using weighted boolean formulas"):
  with members:
    - "inference in probabilistic logic programs using weighted cnf s"
    - "on the implementation of the probabilistic logic programming language problog"
    - "cp logic a language of causal probabilistic events and its relation to logic programming"
    - "a knowledge compilation map"
    - "bayesian logic programs"

Connected through hyperedge HE-5 (induced by source paper "swish swi prolog for sharing"):
  with members:
    - "pengines web logic programming made easy"
    - "pldoc wiki style literate programming for prolog"

Connected through hyperedge HE-6 (induced by source paper "incremental tabling in support of knowledge representation and reasoning"):
  with members:
    - "efficient tabling of structured data with enhanced hash consing"
    - "xsb extending prolog with tabled logic programming"
    - "a three valued semantics for logic programmers"

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)