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 specific term recommendation systems"
  Abstract: In this paper we present the IRSA framework that enables the automatic creation of search term suggestion or recommendation systems (TS). Such TS are used to operationalize interactive query expansion and help users in refining their information need in the query formulation phase. Our recent research has shown TS to be more effective when specific to a certain domain. The presented technical framework allows owners of Digital Libraries to create their own specific TS constructed via OAI-harvested metadata with very little effort.

Connected through hyperedge HE-1 (induced by source paper "a usefulness based approach for measuring the local and global effect of iir services"):
  with members:
    - "whose a tool for whole session analysis in iir"
    - "improving retrieval results with discipline specific query expansion"
    - "a novel combined term suggestion service for domain specific digital libraries"
    - "science models as value added services for scholarly information systems"

Connected through hyperedge HE-2 (induced by source paper "query expansion for survey question retrieval in the social sciences"):
  with members:
    - "thesoz a skos representation of the thesaurus for the social sciences"
    - "a novel combined term suggestion service for domain specific digital libraries"

Connected through hyperedge HE-3 (induced by source paper "are topic specific search term journal name and author name recommendations relevant for researchers"):
  with members:
    - "bibliometric enhanced information retrieval"
    - "extending term suggestion with author names"
    - "a novel combined term suggestion service for domain specific digital libraries"
    - "science models as value added services for scholarly information systems"

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)