| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10322514 | Expert Systems with Applications | 2012 | 6 Pages |
Abstract
⺠Sentiment mining for analyzing short message service (SMS) texts in teaching evaluation. ⺠Data preparation involves the reading, parsing and categorization of the SMS texts. ⺠Three models were developed: the base model, the “corrected” model and the “sentiment” model. ⺠An “interestingness” criterion selects the “sentiment” model.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Chee Kian Leong, Yew Haur Lee, Wai Keong Mak,