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 "using search engine technology to improve library catalogs"):
  Abstract: This chapter outlines how search engine technology can be used in online public access catalogs (OPACs) to help improve users’ experiences, to identify users’ intentions, and to indicate how it can be applied in the library context, along with how sophisticated ranking criteria can be applied to the online library catalog. A review of the literature and the current OPAC developments forms the basis of recommendations on how to improve OPACs. Findings were that the major shortcomings of current OPACs are that they are not sufficiently user-centered and that their results presentations lack sophistication. Furthermore, these shortcomings are not addressed in current 2.0 developments. It is argued that OPAC development should be made search-centered before additional features are applied. Although the recommendations on ranking functionality and the use of user intentions are only conceptual and not yet applied to a library catalogue, practitioners will find recommendations for developing better OPACs in this chapter. In short, readers will find a systematic view on how the search engines’ strengths can be applied to improving libraries’ online catalogs.

Includes members:
  Member "ranking library materials":
    also connected through other hyperedges:
      (none)
  Member "problems with the use of web search engines to find results in foreign languages":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "can we use google scholar to identify highly cited documents")
  Member "the retrieval effectiveness of search engines on navigational queries":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "what users see structures in search engine results pages")
  Member "the retrieval effectiveness of web search engines considering results descriptions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "featured snippets results in google web search an exploratory study")

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.DL(Digital Libraries)