Name
Abstract | ||
|---|---|---|
This paper describes ongoing research on the use of genetic programming to learn term-weighting schemes to be used for text classification. A term-weighting scheme (TWS) determines the way in which documents are represented before applying a text classification model. We propose a genetic program that aims at learning an effective TWS that can improve the performance in text classification. We report preliminary experimental results that give evidence of the validity of the proposal. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2598394.2602286 | GECCO (Companion) |
Keywords | Field | DocType |
representation learning,text classification,automatic programming,gp,natural language processing | Weighting,Computer science,Genetic programming,Artificial intelligence,Text categorization,Machine learning,Feature learning,Genetic program | Conference |
Citations | PageRank | References |
2 | 0.36 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mauricio Garcia-Limon | 1 | 16 | 1.94 |
| Hugo Jair Escalante | 2 | 939 | 73.89 |
| Manuel Montes-Y-Gómez | 3 | 638 | 83.97 |
| Alicia Morales-Reyes | 4 | 70 | 11.55 |
| Eduardo F. Morales | 5 | 559 | 57.67 |