Concept formation by incremental conceptual clustering (1989)
| Venue: | In Proceedings of the International Joint Conference Artificial Intelligence |
| Citations: | 9 - 0 self |
BibTeX
@INPROCEEDINGS{Hadzikadic89conceptformation,
author = {Mirsad Hadzikadic and David Y. Y. Yun},
title = {Concept formation by incremental conceptual clustering},
booktitle = {In Proceedings of the International Joint Conference Artificial Intelligence},
year = {1989},
pages = {831--836},
publisher = {Morgan Kaufmann}
}
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Abstract
Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the problem of knowledge acquisition for knowledge-based systems. In this paper we have described INC, a program that generates a hierarchy of concept descriptions incrementally. INC searches a space of classification hierarchies in both top-down and bottom-up fashion. The system was evaluated along four dimensions and tested in two domains: universities and countries. 1.
Citations
| 569 | DH: Knowledge Acquisition via Incremental Conceptual Clustering - Fisher - 1987 |
| 232 | R.E.: Learning from observation: Conceptual clustering - Michalski, Stepp - 1984 |
| 110 | Rvtrioval and Organizational Strategies in Conceptual Memory. A Computer ' Model - Kolodner - 1980 |
| 90 | Experiments With Incremental Concept Formation - Lebowitz - 1987 |
| 67 | Family Resemblances - Rosch, Mervis - 1975 |
| 46 | Conceptual Clustering: Inventing Goal-Oriented Classifications of Structured Objects - Stepp, Michalski - 1986 |
| 43 | Approaches to conceptual clustering - Fisher, Langley - 1985 |
| 4 | Concept Formation by Goal-Driven, Context-Dependent Classification - Hadzikadic - 1988 |
| 1 | Concept Formation by Heuristic Classification. Doctoral Dissertation - Hadzikadic - 1987 |
