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: "large scale citation matching using apache hadoop"
  Abstract: During the process of citation matching links from bibliography entries to referenced publications are created. Such links are indicators of topical similarity between linked texts, are used in assessing the impact of the referenced document and improve navigation in the user interfaces of digital libraries. In this paper we present a citation matching method and show how to scale it up to handle great amounts of data using appropriate indexing and a MapReduce paradigm in the Hadoop environment.

Connected through hyperedge HE-1 (induced by source paper "machine learning vs rules and out of the box vs retrained an evaluation of open source bibliographic reference and citation parsers"):
  with members:
    - "mr dlib recommendations as a service raas for academia"
    - "semantic publishing challenge assessing the quality of scientific output by information extraction and interlinking"

Connected through hyperedge HE-2 (induced by source paper "parsrec a novel meta learning approach to recommending bibliographic reference parsers"):
  with members:
    - "mr dlib recommendations as a service raas for academia"

Connected through hyperedge HE-3 (induced by source paper "taming the zoo about algorithms implementation in the ecosystem of apache hadoop"):
  with members:
    - "how to perform research in hadoop environment not losing mental equilibrium case study"
    - "mapreduce is good enough if all you have is a hammer throw away everything that s not a nail"

Connected through hyperedge HE-4 (induced by source paper "how to perform research in hadoop environment not losing mental equilibrium case study"):
  with members:
    - "taming the zoo about algorithms implementation in the ecosystem of apache hadoop"

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)