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 "unsupervised formation matching in highly inflected languages"):
  Abstract: There have been multiple attempts to resolve the various formation matching problem in information retrieval. Stemming is a common strategy to this end. Among many approaches for stemming, statistical stemming has shown to be effective in a few number of languages, particularly those highly inflected ones. Common statistical approaches heavily relies on string similarity in terms of prefix and suffix matching. In this paper we propose a method that is able to find any popular affix in any position of a word; specifically finding infixes is a required task in Persian, Arabic, and Malay particularly in irregular formations and is a future challenge in informal texts. The proposed method aims at finding a number of transformation rules for expanding a word with its inflectional/derivation formations. Our experimental results on CLEF 2008 and CLEF 2009 English-Persian CLIR tasks indicate that the proposed method significantly outperforms all the baselines in terms of MAP.

Includes members:
  Member "dimension projection among languages based on pseudo relevant documents for query translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "low dimensional query projection based on divergence minimization feedback model for ad hoc retrieval")
  Member "a probabilistic translation method for dictionary based cross lingual information retrieval in agglutinative languages":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ss4mct a statistical stemmer for morphologically complex texts")

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.IR(Information Retrieval)