Text Classification for literature search of research study designs
- Authors
- Galarza Quishpe, Eddie Daniel
- Format
- MasterThesis
- Status
- publishedVersion
- Description
Information search is used every day in many fields of the human labors. The information found is needed as evidence for making decisions. In healthcare, information has also become a necessity to find the best path to invest into a health program. Some organizations like the Health Technology Assessment have developed alternatives to find this information provided by life sciences and biomedical records. A manual technique could give the support for finding concrete information like ?health economic evaluations? by looking at the terms contained in the records. However, this technique does not provide high levels of accuracy. In this research it is proposed an alternative to contrast manual techniques by using an automatic machine learning approach. Classification is the method from machine learning used to achieve the information search task. It has been proven that it can give acceptable levels of accuracy as well as providing proof that terms analysis can be used to determine the category of a record. Moreover, the use of a good classification algorithm and different combinations of features could give an efficient model that contrasts a manually developed technique.
- Publication Year
- 2015
- Language
- eng
- Topic
- INFORM?TICA
APLICACI?N INFORM?TICA
PROCESAMIENTO DE DATOS
PROCESAMIENTO DE PALABRAS
INVESTIGACI?N
CLASIFICACI?N DIGITAL
- Repository
- Repositorio SENESCYT
- Rights
- openAccess
- License