| Author | Title | Year | Journal/Proceedings | Reftype | DOI/URL |
|---|---|---|---|---|---|
| Fisher, D. H. | Knowledge Acquisition Via Incremental Conceptual Clustering | 1987 | Machine Learning | article | URL |
| 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.
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BibTeX:
@article{h1987knowledge,
author = {Fisher, Douglas H.},
title = {Knowledge Acquisition Via Incremental Conceptual Clustering},
journal = {Machine Learning},
year = {1987},
volume = {2},
number = {2},
pages = {139--172},
url = {http://dx.doi.org/10.1023/A:1022852608280}
}
|
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| Fisher, D. H. | Knowledge Acquisition Via Incremental Conceptual Clustering | 1987 | Machine Learning | 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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