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 framework for evaluating the retrieval effectiveness of search engines"
  Abstract: This chapter presents a theoretical framework for evaluating next generation search engines. We focuson search engines whose results presentation is enriched with additional information and does notmerely present the usual list of “10 blue links”, that is, of ten links to results, accompanied by a shortdescription. While Web search is used as an example here, the framework can easily be applied tosearch engines in any other area.The framework not only addresses the results presentation, but also takes into account an extension ofthe general design of retrieval effectiveness tests. The chapter examines the ways in which this designmight influence the results of such studies and how a reliable test is best designed.

Connected through hyperedge HE-1 (induced by source paper "credibility in web search engines"):
  with members:
    - "what users see structures in search engine results pages"
    - "the retrieval effectiveness of web search engines considering results descriptions"
    - "ranking of wikipedia articles in search engines revisited fair ranking for reasonable quality"

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)