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: "scientometrics and information retrieval weak links revitalized"
  Abstract: This special issue brings together eight papers from experts of communities which often have been perceived as different once: bibliometrics, scientometrics and informetrics on the one side and information retrieval on the other. The idea of this special issue started at the workshop "Combining Bibliometrics and Information Retrieval" held at the 14th International Conference of Scientometrics and Informetrics, Vienna, July 14---19, 2013. Our motivation as guest editors started from the observation that main discourses in both fields are different, that communities are only partly overlapping and from the belief that a knowledge transfer would be profitable for both sides.

Connected through hyperedge HE-1 (induced by source paper "report on the 8th international workshop on bibliometric enhanced information retrieval bir 2019"):
  with members:
    - "improving scientific article visibility by neural title simplification"
    - "discovering seminal works with marker papers"

Connected through hyperedge HE-2 (induced by source paper "analysis of search stratagem utilisation"):
  with members:
    - "investigating exploratory search activities based on the stratagem level in digital libraries"
    - "contextualised browsing in a digital library s living lab"
    - "analysis of footnote chasing and citation searching in an academic search engine"
    - "a complete year of user retrieval sessions in a social sciences academic search engine"
    - "a usefulness based approach for measuring the local and global effect of iir services"
    - "extending search facilities via bibliometric enhanced stratagems"
    - "science models as value added services for scholarly information systems"

Connected through hyperedge HE-3 (induced by source paper "report on the 7th international workshop on bibliometric enhanced information retrieval bir 2018"):
  with members:
    - "bibliometric enhanced information retrieval"

Connected through hyperedge HE-4 (induced by source paper "contextualization of topics browsing through the universe of bibliographic information"):
  with members:
    - "citation based clustering of publications using citnetexplorer and vosviewer"
    - "mutual information based labelling and comparing clusters"
    - "clustering articles based on semantic similarity"
    - "ariadne s thread interactive navigation in a world of networked information"
    - "contextualization of topics browsing through terms authors journals and cluster allocations"
    - "the semantic mapping of words and co words in contexts"

Connected through hyperedge HE-5 (induced by source paper "bibliometrics and information retrieval creating knowledge through research synergies"):
  with members:
    - "bibliometric enhanced information retrieval 5th international bir workshop"

Connected through hyperedge HE-6 (induced by source paper "research project text engineering tool for ontological scientometry"):
  with members:
    - "experimental economics for web mining"

Connected through hyperedge HE-7 (induced by source paper "bibliometric enhanced information retrieval 5th international bir workshop"):
  with members:
    - "evaluating co authorship networks in author name disambiguation for common names"
    - "science models as value added services for scholarly information systems"

Connected through hyperedge HE-8 (induced by source paper "editorial for the first workshop on mining scientific papers computational linguistics and bibliometrics"):
  with members:
    - "classification of research citations crc"

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)