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: "a probabilistic translation method for dictionary based cross lingual information retrieval in agglutinative languages"
  Abstract: School of Electrical and Computer Engineering,College of Engineering,University of Tehran, Tehran, Iran.{dadashkarimi,shakery,hfaili}@ut.ac.irAbstract. Translation ambiguity, out of vocabulary words and missingsome translations in bilingual dictionaries make dictionary-based Cross-language Information Retrieval (CLIR) a challenging task. Moreover,in agglutinative languages which do not have reliable stemmers, miss-ing various lexical formations in bilingual dictionaries degrades CLIRperformance. This paper aims to introduce a probabilistic translationmodel to solve the ambiguity problem, and also to provide most likelyformations of a dictionary candidate. We propose Minimum Edit Sup-port Candidates (MESC) method that exploits a monolingual corpusand a bilingual dictionary to translate users’ native language queries todocuments’ language. Our experiments show that the proposed methodoutperforms state-of-the-art dictionary-based English-Persian CLIR.

Connected through hyperedge HE-1 (induced by source paper "ss4mct a statistical stemmer for morphologically complex texts"):
  with members:
    - "dimension projection among languages based on pseudo relevant documents for query translation"

Connected through hyperedge HE-2 (induced by source paper "unsupervised formation matching in highly inflected languages"):
  with members:
    - "dimension projection among languages based on pseudo relevant documents for query 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.IR(Information Retrieval)