Concept Formation by Incremental Conceptual Clustering
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.
Cite
Text
Hadzikadic and Yun. "Concept Formation by Incremental Conceptual Clustering." International Joint Conference on Artificial Intelligence, 1989.Markdown
[Hadzikadic and Yun. "Concept Formation by Incremental Conceptual Clustering." International Joint Conference on Artificial Intelligence, 1989.](https://mlanthology.org/ijcai/1989/hadzikadic1989ijcai-concept/)BibTeX
@inproceedings{hadzikadic1989ijcai-concept,
title = {{Concept Formation by Incremental Conceptual Clustering}},
author = {Hadzikadic, Mirsad and Yun, David Y. Y.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1989},
pages = {831-836},
url = {https://mlanthology.org/ijcai/1989/hadzikadic1989ijcai-concept/}
}