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: "provenance as dependency analysis"
  Abstract: Provenance is information recording the source, derivation, or history of some information. Provenance tracking has been studied in a variety of settings; however, although many design points have been explored, the mathematical or semantic foundations of data provenance have received comparatively little attention. In this paper, we argue that dependency analysis techniques familiar from program analysis and program slicing provide a formal foundation for forms of provenance that are intended to show how (part of) the output of a query depends on (parts of) its input. We introduce a semantic characterization of such dependency provenance, show that this form of provenance is not computable, and provide dynamic and static approximation techniques.

Connected through hyperedge HE-1 (induced by source paper "the relationship between trust in ai and trustworthy machine learning technologies"):
  with members:
    - "decision provenance harnessing data flow for accountable systems"
    - "the measure and mismeasure of fairness a critical review of fair machine learning"
    - "methods for interpreting and understanding deep neural networks"
    - "sok security and privacy in machine learning"
    - "yes machine learning can be more secure a case study on android malware detection"
    - "interpretable explorable approximations of black box models"
    - "a unified approach to interpreting model predictions"
    - "learning important features through propagating activation differences"

Connected through hyperedge HE-2 (induced by source paper "responsibility analysis by abstract interpretation"):
  with members:
    - "a relational logic for higher order programs"
    - "cause clue clauses error localization using maximum satisfiability"
    - "what causes a system to satisfy a specification"
    - "responsibility and blame a structural model approach"

Connected through hyperedge HE-3 (induced by source paper "using a model driven approach in building a provenance framework for tracking policy making processes in smart cities"):
  with members:
    - "model driven development of complex software a research roadmap"

Connected through hyperedge HE-4 (induced by source paper "language integrated provenance"):
  with members:
    - "database queries that explain their work"
    - "effective quotation relating approaches to language integrated query"
    - "first class functions for first order database engines"
    - "provenance for aggregate queries"

Connected through hyperedge HE-5 (induced by source paper "database queries that explain their work"):
  with members:
    - "a core calculus for provenance"
    - "putting lipstick on pig enabling database style workflow provenance"
    - "provenance for aggregate queries"

Connected through hyperedge HE-6 (induced by source paper "a core calculus for provenance"):
  with members:
    - "surrogate parenthood protected and informative graphs"
    - "causality and the semantics of provenance"
    - "provenance views for module privacy"
    - "causes and explanations a structural model approach part ii explanations"

Connected through hyperedge HE-7 (induced by source paper "mathematical practice crowdsourcing and social machines"):
  with members:
    - "theorem proving in large formal mathematics as an emerging ai field"

Connected through hyperedge HE-8 (induced by source paper "causality and the semantics of provenance"):
  with members:
    - "causes and explanations in the structural model approach tractable cases"
    - "causes and explanations a structural model approach part ii explanations"

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.DB(Databases)