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    AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
    Fisher, D.H. Knowledge Acquisition Via Incremental Conceptual Clustering 1987 Machine Learning
    Vol. 2(2), pp. 139-172 
    article  
    Abstract: Conceptual clustering is an important way of summarizing and explaining data. However, the recent formulation of this paradigm has allowed little exploration of conceptual clustering as a means of improving performance. Furthermore, previous work in conceptual clustering has not explicitly dealt with constraints imposed by real world environments. This article presents COBWEB, a conceptual clustering system that organizes data so as to maximize inference ability. Additionally, COBWEB is incremental and computationally economical, and thus can be flexibly applied in a variety of domains.
    BibTeX:
    @article{fischer87,
      author = {Fisher, Douglas H.},
      title = {Knowledge Acquisition Via Incremental Conceptual Clustering},
      journal = {Machine Learning},
      year = {1987},
      volume = {2},
      number = {2},
      pages = {139--172}
    }
    

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