Semantic Enrichment of Relevant Feature Selection Methods for Data Mining in Oncology

Adriana Da Silva Jacinto, Ricardo Da Silva Santos, José Maria Parente De Oliveira

Abstract

This project presents a proposal of capturing of the semantic importance of each feature by computational manner. The proposal enriches the traditional methods of feature selection by using of Natural Language Processing, the NCI ontology, WordNet and medical documents. A prototype of this approach was implemented and tested with five data sets related to cancer patients. The results show that the use of semantic improves the pre – processing by selecting of the most relevant semantic features.

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Paper Citation


in Harvard Style

Da Silva Jacinto A., Da Silva Santos R. and Parente De Oliveira J. (2014). Semantic Enrichment of Relevant Feature Selection Methods for Data Mining in Oncology . In Doctoral Consortium - DC3K, (IC3K 2014) ISBN Not Available, pages 24-30. DOI: 10.5220/0005172400240030


in Bibtex Style

@conference{dc3k14,
author={Adriana Da Silva Jacinto and Ricardo Da Silva Santos and José Maria Parente De Oliveira},
title={Semantic Enrichment of Relevant Feature Selection Methods for Data Mining in Oncology},
booktitle={Doctoral Consortium - DC3K, (IC3K 2014)},
year={2014},
pages={24-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005172400240030},
isbn={Not Available},
}


in EndNote Style

TY - CONF
JO - Doctoral Consortium - DC3K, (IC3K 2014)
TI - Semantic Enrichment of Relevant Feature Selection Methods for Data Mining in Oncology
SN - Not Available
AU - Da Silva Jacinto A.
AU - Da Silva Santos R.
AU - Parente De Oliveira J.
PY - 2014
SP - 24
EP - 30
DO - 10.5220/0005172400240030