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: "recognition performance of a structured language model"
  Abstract: A new language model for speech recognition inspired by linguistic analysis is presented. The model develops hidden hierarchical structure incrementally and uses it to extract meaningful information from the word history - thus enabling the use of extended distance dependencies - in an attempt to complement the locality of currently used trigram models. The structured language model, its probabilistic parameterization and performance in a two-pass speech recognizer are presented. Experiments on the SWITCHBOARD corpus show an improvement in both perplexity and word error rate over conventional trigram models.

Connected through hyperedge HE-1 (induced by source paper "probabilistic top down parsing and language modeling"):
  with members:
    - "exploiting syntactic structure for natural language modeling"
    - "exploiting diversity in natural language processing combining parsers"
    - "estimators for stochastic unification based grammars"
    - "efficient probabilistic top down and left corner parsing"
    - "measuring efficiency in high accuracy broad coverage statistical parsing"
    - "refinement of a structured language model"
    - "expoiting syntactic structure for language modeling"

Connected through hyperedge HE-2 (induced by source paper "robust probabilistic predictive syntactic processing"):
  with members:
    - "probabilistic top down parsing and language modeling"
    - "exploiting syntactic structure for natural language modeling"
    - "compact non left recursive grammars using the selective left corner transform and factoring"
    - "efficient probabilistic top down and left corner parsing"
    - "measuring efficiency in high accuracy broad coverage statistical parsing"
    - "refinement of a structured language model"
    - "expoiting syntactic structure for language modeling"

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)