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: "role of temporal inference in the recognition of textual inference"
  Abstract: This project is a part of nature language processing and its aims to develop a system of recognition inference text-appointed TIMINF. This type of system can detect, given two portions of text, if a text is semantically deducted from the other. We focused on making the inference time in this type of system. For that we have built and analyzed a body built from questions collected through the web. This study has enabled us to classify different types of times inferences and for designing the architecture of TIMINF which seeks to integrate a module inference time in a detection system inference text. We also assess the performance of sorties TIMINF system on a test corpus with the same strategy adopted in the challenge RTE.

Connected through hyperedge HE-1 (induced by source paper "hybrid q learning applied to ubiquitous recommender system"):
  with members:
    - "applying machine learning techniques to improve user acceptance on ubiquitous environement"
    - "empirical analysis of predictive algorithms for collaborative filtering"
    - "situation aware approach to improve context based recommender system"
    - "optimizing an utility function for exploration exploitation trade off in context aware recommender system"

Connected through hyperedge HE-2 (induced by source paper "improving adaptation of ubiquitous recommander systems by using reinforcement learning and collaborative filtering"):
  with members:
    - "applying machine learning techniques to improve user acceptance on ubiquitous environement"
    - "empirical analysis of predictive algorithms for collaborative filtering"
    - "situation aware approach to improve context based recommender system"
    - "optimizing an utility function for exploration exploitation trade off in context aware recommender system"

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.CL(Computation and Language)