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: "polish english speech statistical machine translation systems for the iwslt 2013"
  Abstract: This research explores the effects of various training settings from Polish to English Statistical Machine Translation system for spoken language. Various elements of the TED parallel text corpora for the IWSLT 2013 evaluation campaign were used as the basis for training of language models, and for development, tuning and testing of the translation system. The BLEU, NIST, METEOR and TER metrics were used to evaluate the effects of data preparations on translation results. Our experiments included systems, which use stems and morphological information on Polish words. We also conducted a deep analysis of provided Polish data as preparatory work for the automatic data correction and cleaning phase.

Connected through hyperedge HE-1 (induced by source paper "polish english speech statistical machine translation systems for the iwslt 2014"):
  with members:
    - "a sentence meaning based alignment method for parallel text corpora preparation"
    - "real time statistical speech translation"
    - "enhanced bilingual evaluation understudy"
    - "neural machine translation by jointly learning to align and translate"

Connected through hyperedge HE-2 (induced by source paper "neural based machine translation for medical text domain based on european medicines agency leaflet texts"):
  with members:
    - "enhanced bilingual evaluation understudy"
    - "neural machine translation by jointly learning to align and translate"
    - "learning phrase representations using rnn encoder decoder for statistical machine translation"

Connected through hyperedge HE-3 (induced by source paper "noisy parallel and comparable corpora filtering methodology for the extraction of bi lingual equivalent data at sentence level"):
  with members:
    - "a sentence meaning based alignment method for parallel text corpora preparation"
    - "real time statistical speech translation"

Connected through hyperedge HE-4 (induced by source paper "unsupervised comparable corpora preparation and exploration for bi lingual translation equivalents"):
  with members:
    - "real time statistical speech translation"

Connected through hyperedge HE-5 (induced by source paper "spoken language translation for polish"):
  with members:
    - "real time statistical speech translation"

Connected through hyperedge HE-6 (induced by source paper "enhancements in statistical spoken language translation by de normalization of asr results"):
  with members:
    - "real time statistical speech translation"

Connected through hyperedge HE-7 (induced by source paper "building subject aligned comparable corpora and mining it for truly parallel sentence pairs"):
  with members:
    - "a sentence meaning based alignment method for parallel text corpora preparation"
    - "real time statistical speech translation"

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)