| Full text | |
| Author(s): |
Eler, Danilo Medeiros
[1]
;
Grosa, Denilson
[1]
;
Pola, Ives
[2]
;
Garcia, Rogerio
[1]
;
Correia, Ronaldo
[1]
;
Teixeira, Jaqueline
[1]
Total Authors: 6
|
| Affiliation: | [1] Sao Paulo State Univ UNESP, Dept Matemat & Comp, BR-19060900 Presidente Prudente - Brazil
[2] Univ Technol UTFPR, Dept Informat, BR-85503390 Pato Branco - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | INFORMATION; v. 9, n. 4 APR 2018. |
| Web of Science Citations: | 1 |
| Abstract | |
Typically, textual information is available as unstructured data, which require processing so that data mining algorithms can handle such data; this processing is known as the pre-processing step in the overall text mining process. This paper aims at analyzing the strong impact that the pre-processing step has on most mining tasks. Therefore, we propose a methodology to vary distinct combinations of pre-processing steps and to analyze which pre-processing combination allows high precision. In order to show different combinations of pre-processing methods, experiments were performed by comparing some combinations such as stemming, term weighting, term elimination based on low frequency cut and stop words elimination. These combinations were applied in text and opinion mining tasks, from which correct classification rates were computed to highlight the strong impact of the pre-processing combinations. Additionally, we provide graphical representations from each pre-processing combination to show how visual approaches are useful to show the processing effects on document similarities and group formation (i.e., cohesion and separation). (AU) | |
| FAPESP's process: | 13/03452-0 - An extensible coordination model for coordinated and multiple views and approaches to aid the visual analysis process |
| Grantee: | Danilo Medeiros Eler |
| Support Opportunities: | Regular Research Grants |