Be Certain of How-to Before Mining Uncertain Data
Abstract
The purpose of this technical note is to introduce the problems of similarity detection and summarization in uncertain data. We provide the essential arguments that make the problems relevant to the data-mining and machine-learning community, stating major issues and summarizing our contributions in the field. Further challenges and directions of research are also issued.
Cite
Text
Gullo et al. "Be Certain of How-to Before Mining Uncertain Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014. doi:10.1007/978-3-662-44845-8_42Markdown
[Gullo et al. "Be Certain of How-to Before Mining Uncertain Data." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2014.](https://mlanthology.org/ecmlpkdd/2014/gullo2014ecmlpkdd-certain/) doi:10.1007/978-3-662-44845-8_42BibTeX
@inproceedings{gullo2014ecmlpkdd-certain,
title = {{Be Certain of How-to Before Mining Uncertain Data}},
author = {Gullo, Francesco and Ponti, Giovanni and Tagarelli, Andrea},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2014},
pages = {489-493},
doi = {10.1007/978-3-662-44845-8_42},
url = {https://mlanthology.org/ecmlpkdd/2014/gullo2014ecmlpkdd-certain/}
}