A Bibliographic View on Constrained Clustering

Autor:	Kuncheva, Ludmila, Williams, Francis, Hennessey, Samuel
Rok vydání:	2022
Předmět:	Computer Science - Machine Learning Computer Science - Information Retrieval 62H30 I.5.3 I.5.0
Druh dokumentu:	Working Paper
Popis:	A keyword search on constrained clustering on Web-of-Science returned just under 3,000 documents. We ran automatic analyses of those, and compiled our own bibliography of 183 papers which we analysed in more detail based on their topic and experimental study, if any. This paper presents general trends of the area and its sub-topics by Pareto analysis, using citation count and year of publication. We list available software and analyse the experimental sections of our reference collection. We found a notable lack of large comparison experiments. Among the topics we reviewed, applications studies were most abundant recently, alongside deep learning, active learning and ensemble learning. Comment: 18 pages, 11 figures, 177 references
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2209.11125 Zobrazit plný text záznamu View this record from Arxiv