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: "the lumiere project bayesian user modeling for inferring the goals and needs of software users"
  Abstract: The Lumiere Project centers on harnessing probability and utility to provide assistance to computer software users. We review work on Bayesian user models that can be employed to infer a users needs by considering a user's background, actions, and queries. Several problems were tackled in Lumiere research, including (1) the construction of Bayesian models for reasoning about the time-varying goals of computer users from their observed actions and queries, (2) gaining access to a stream of events from software applications, (3) developing a language for transforming system events into observational variables represented in Bayesian user models, (4) developing persistent profiles to capture changes in a user expertise, and (5) the development of an overall architecture for an intelligent user interface. Lumiere prototypes served as the basis for the Office Assistant in the Microsoft Office '97 suite of productivity applications.

Connected through hyperedge HE-1 (induced by source paper "investigating classification techniques with feature selection for intention mining from twitter feed"):
  with members:
    - "feature selection a data perspective"
    - "emotion intensities in tweets"
    - "characterizing linguistic attributes for automatic classification of intent based racist radicalized posts on tumblr micro blogging website"

Connected through hyperedge HE-2 (induced by source paper "stuck no worries task aware command recommendation and proactive help for analysts"):
  with members:
    - "intent aware contextual recommendation system"
    - "topically driven neural language model"
    - "learning to attend copy and generate for session based query suggestion"
    - "topicrnn a recurrent neural network with long range semantic dependency"
    - "adam a method for stochastic optimization"
    - "sequence to sequence learning with neural networks"

Connected through hyperedge HE-3 (induced by source paper "attention sensitive alerting"):
  with members:
    - "time dependent utility and action under uncertainty"
    - "empirical analysis of predictive algorithms for collaborative filtering"

Connected through hyperedge HE-4 (induced by source paper "probabilistic models for agents beliefs and decisions"):
  with members:
    - "from influence diagrams to junction trees"
    - "accounting for context in plan recognition with application to traffic monitoring"

Connected through hyperedge HE-5 (induced by source paper "building a stochastic dynamic model of application use"):
  with members:
    - "decision theoretic planning structural assumptions and computational leverage"

Connected through hyperedge HE-6 (induced by source paper "conversation as action under uncertainty"):
  with members:
    - "dynamic network models for forecasting"

Connected through hyperedge HE-7 (induced by source paper "toward experiential utility elicitation for interface customization"):
  with members:
    - "utility elicitation as a classification problem"

Connected through hyperedge HE-8 (induced by source paper "aides en ligne a l utilisation de logiciels grand public probl emes sp ecifiques de conception et solutions potentielles"):
  with members:
    - "viewpoints in co design a field study in concurrent engineering"
    - "do oral messages help visual search"

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)