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: "co occurrence matrices and their applications in information science extending aca to the web environment"
  Abstract: Co-occurrence matrices, such as co-citation, co-word, and co-link matrices, have been used widely in the information sciences. However, confusion and controversy have hindered the proper statistical analysis of this data. The underlying problem, in our opinion, involved understanding the nature of various types of matrices. This paper discusses the difference between a symmetrical co-citation matrix and an asymmetrical citation matrix as well as the appropriate statistical techniques that can be applied to each of these matrices, respectively. Similarity measures (like the Pearson correlation coefficient or the cosine) should not be applied to the symmetrical co-citation matrix, but can be applied to the asymmetrical citation matrix to derive the proximity matrix. The argument is illustrated with examples. The study then extends the application of co-occurrence matrices to the Web environment where the nature of the available data and thus data collection methods are different from those of traditional databases such as the Science Citation Index. A set of data collected with the Google Scholar search engine is analyzed using both the traditional methods of multivariate analysis and the new visualization software Pajek that is based on social network analysis and graph theory.

Connected through hyperedge HE-1 (induced by source paper "the superior knowledge proximity measure for patent mapping"):
  with members:
    - "measuring technological distance for patent mapping"
    - "filtering patent maps for visualization of diversification paths of inventors and organizations"

Connected through hyperedge HE-2 (induced by source paper "mapping patent classifications portfolio and statistical analysis and the comparison of strengths and weaknesses"):
  with members:
    - "measuring technological distance for patent mapping"
    - "strategic intelligence on emerging technologies scientometric overlay mapping"
    - "generating clustered journal maps an automated system for hierarchical classification"
    - "patent portfolio analysis of cities statistics and maps of technological inventiveness"
    - "journal portfolio analysis for countries cities and organizations maps and comparisons"
    - "patents as instruments for exploring innovation dynamics geographic and technological perspectives on photovoltaic cells"
    - "can technology life cycles be indicated by diversity in patent classifications the crucial role of variety"
    - "science visualization and discursive knowledge"

Connected through hyperedge HE-3 (induced by source paper "measuring technological distance for patent mapping"):
  with members:
    - "interactive overlay maps for us patent uspto data based on international patent classifications ipc"
    - "visualization of the citation impact environments of scientific journals an online mapping exercise"

Connected through hyperedge HE-4 (induced by source paper "full and fractional counting in bibliometric networks"):
  with members:
    - "constructing bibliometric networks a comparison between full and fractional counting"
    - "the normalization of co authorship networks in the bibliometric evaluation the government stimulation programs of china and korea"
    - "the normalization of occurrence and co occurrence matrices in bibliometrics using cosine similarities and ochiai coefficients"
    - "network analysis of zentralblatt math data"
    - "a systematic empirical comparison of different approaches for normalizing citation impact indicators"
    - "on bibliographic networks"

Connected through hyperedge HE-5 (induced by source paper "the normalization of occurrence and co occurrence matrices in bibliometrics using cosine similarities and ochiai coefficients"):
  with members:
    - "journal portfolio analysis for countries cities and organizations maps and comparisons"
    - "similarity measures author cocitation analysis and information theory"

Connected through hyperedge HE-6 (induced by source paper "network maps of technology fields a comparative analysis of relatedness measures"):
  with members:
    - "visualization of the citation impact environments of scientific journals an online mapping exercise"

Connected through hyperedge HE-7 (induced by source paper "an event network for exploring open information"):
  with members:
    - "beating the news with embers forecasting civil unrest using open source indicators"

Connected through hyperedge HE-8 (induced by source paper "resygen a recommendation system generator using domain based heuristics"):
  with members:
    - "measuring the meaning of words in contexts an automated analysis of controversies about monarch butterflies frankenfoods and stem cells"
    - "visualization of the citation impact environments of scientific journals an online mapping exercise"
    - "content based book recommending using learning for text categorization"

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)