human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "classifier based text simplification for improved machine translation"):
  Abstract: Machine Translation is one of the research fields of Computational Linguistics. The objective of many MT Researchers is to develop an MT System that produce good quality and high accuracy output translations and which also covers maximum language pairs. As internet and Globalization is increasing day by day, we need a way that improves the quality of translation. For this reason, we have developed a Classifier based Text Simplification Model for English-Hindi Machine Translation Systems. We have used support vector machines and Na\"ive Bayes Classifier to develop this model. We have also evaluated the performance of these classifiers.

Includes members:
  Member "reordering rules for english hindi smt":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "utilizing language relatedness to improve machine translation a case study on languages of the indian subcontinent")
  Member "quality estimation of machine translation outputs through stemming":
    also connected through other hyperedges:
      (none)
  Member "quality estimation of english hindi outputs using naive bayes classifier":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "quality estimation of machine translation outputs through stemming")
  Member "improving the quality of gujarati hindi machine translation through part of speech tagging and stemmer assisted transliteration":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "quality estimation of machine translation outputs through stemming")
  Member "automatic ranking of mt outputs using approximations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "quality estimation of machine translation outputs through stemming")
  Member "analysing quality of english hindi machine translation engine outputs using bayesian classification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards an arabic english machine translation based on semantic web")
  Member "a lightweight stemmer for gujarati":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "quality estimation of machine translation outputs through stemming")

Question: Please tell me which class the source paper 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)