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: "improving retrieval results with discipline specific query expansion"
  Abstract: Choosing the right terms to describe an information need is becoming more difficult as the amount of available information increases. Search-Term-Recommendation (STR) systems can help to overcome these problems. This paper evaluates the benefits that may be gained from the use of STRs in Query Expansion (QE). We create 17 STRs, 16 based on specific disciplines and one giving general recommendations, and compare the retrieval performance of these STRs. The main findings are: (1) QE with specific STRs leads to significantly better results than QE with a general STR, (2) QE with specific STRs selected by a heuristic mechanism of topic classification leads to better results than the general STR, however (3) selecting the best matching specific STR in an automatic way is a major challenge of this process.

Connected through hyperedge HE-1 (induced by source paper "user interests in german social science literature search a large scale log analysis"):
  with members:
    - "a usefulness based approach for measuring the local and global effect of iir services"

Connected through hyperedge HE-2 (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"
    - "a framework for specific term recommendation systems"
    - "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-3 (induced by source paper "a system for probabilistic linking of thesauri and classification systems"):
  with members:
    - "the polylingual labeled topic model"
    - "enriching ontologies with encyclopedic background knowledge for document indexing"
    - "thesoz a skos representation of the thesaurus for the social sciences"

Connected through hyperedge HE-4 (induced by source paper "corpus analysis without prior linguistic knowledge unsupervised mining of phrases and subphrase structure"):
  with members:
    - "improved semantic representations from tree structured long short term memory networks"
    - "machine learning in automated text categorization"

Connected through hyperedge HE-5 (induced by source paper "a framework for specific term recommendation systems"):
  with members:
    - "a novel combined term suggestion service for domain specific digital libraries"

Connected through hyperedge HE-6 (induced by source paper "dealing with sparse document and topic representations lab report for chic 2012"):
  with members:
    - "extending term suggestion with author names"

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)