Loading...
Please wait, while we are loading the content...
Similar Documents
Classification Scheme of Unstructured Text Document using TF-IDF and Naive Bayes Classifier
| Content Provider | Semantic Scholar |
|---|---|
| Author | Yoo, Jong-Yeol Yang, Dongmin |
| Copyright Year | 2015 |
| Abstract | Recently due to large-scale data spread in digital economy, the era of big data is coming. Through big data, unstructured text data consisting of technical text document, confidential document, false information documents are experiencing serious problems in the runoff. To prevent this, the need of art to sort and process the document consisting of text data has increased. In this paper, we propose a novel text classification scheme which learns some data sets and correctly classifies unstructured text data into two different categories, True and False. The proposed method is implemented using Naive Bayes document classifier and TF-IDF. |
| Starting Page | 263 |
| Ending Page | 266 |
| Page Count | 4 |
| File Format | PDF HTM / HTML |
| DOI | 10.14257/astl.2015.111.50 |
| Alternate Webpage(s) | http://onlinepresent.org/proceedings/vol111_2015/50.pdf |
| Alternate Webpage(s) | https://doi.org/10.14257/astl.2015.111.50 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
