@inproceedings{59d2966b4dfb4b86944222e394fdfd2a,
title = "Case-based classification on hierarchical structure of formal concept analysis",
abstract = "We propose a novel Hierarchical CBC model (HCBC) based on Formal Concept Analysis (FCA). Firstly, Concept Lattice (CL), the hierarchical and conceptual structure in FCA, is adopted to represent cases. Thus a novel dynamic weight model is proposed from CL to measure similarities between cases and concepts. Then the similarity metric is applied to retrieve the top-K similar concepts which are used to vote for adaptive solutions for new cases by ma-jority voting in case adaption. Experiments show our model shows good performance in terms of accuracy and outperforms the other classification methods.",
author = "Qi Zhang and Chongyang Shi and Ping Sun and Zhengdong Niu",
note = "Publisher Copyright: {\textcopyright} 2016 The Authors and IOS Press.; 22nd European Conference on Artificial Intelligence, ECAI 2016 ; Conference date: 29-08-2016 Through 02-09-2016",
year = "2016",
doi = "10.3233/978-1-61499-672-9-1758",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "1758--1759",
editor = "Kaminka, {Gal A.} and Maria Fox and Paolo Bouquet and Eyke Hullermeier and Virginia Dignum and Frank Dignum and {van Harmelen}, Frank",
booktitle = "Frontiers in Artificial Intelligence and Applications",
address = "Netherlands",
}