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: "monotone precision and recall measures for comparing executions and specifications of dynamic systems"
  Abstract: The comparison of the behaviours of software systems is an important concern in software engineering research. For example, in the areas of specification discovery and specification mining, it is important to measure the consistency between a collection of execution traces and the program specification that was automatically constructed from these traces. This problem is also tackled in process mining, where for almost two decades researchers propose measures to assess the quality of process specifications automatically discovered from execution logs of information systems. Though various measures have been proposed, it was recently observed that none of them fulfils essential properties, such as monotonicity. To address this research problem, we build on the following observation: If two behaviours are not equivalent, the extent of deviation can be quantified by a quotient of a certain aspect of one behaviour over the same aspect of the other behaviour. However, there is no systematic approach for defining such quotients and it is unclear which aspects shall be considered for meaningful comparison of systems that describe infinite behaviours. We demonstrate the application of the quotients to capture precision and recall between a collection of recorded executions of a system and a system specification, i.e., between the recorded and specified behaviours of a system. An experimental evaluation of the quotients using our open-source implementation demonstrates their feasibility and indicates that they enable a monotonic assessment.

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.FL(Formal Languages and Automata Theory)