Document classification is a good example of Machine Learning in the form of Natural Language Processing. It is a worth your attention process that would reduce time of searching and retrieving essential data. It quickly separates important information from insignificant text.
The process of assigning documents to categories is based on pre-trained data models. Our text2data tool detects documents in 26 categories - we call it "auto-categories".
We also provide our users with the ability to train their own document categorization models, the analysis results based on such a user pre-trained models are displayed separately - we call it "user categories".
Following auto categories are being detected [IAB QAG taxonomy]
IAB code | Category name |
IAB2 | Automotive |
IAB1-1 | Books and Literature |
IAB13-3 | Business and Finance |
IAB1-3 | Fine Art |
IAB8 | Food & Drink |
IAB7-35 | Healthy Living/ Children's Health |
IAB9-2 | Hobbies & Interests/ Arts & Crafts |
IAB9-16 | Hobbies & Interests/ Musical Instruments |
IAB10 | Home & Garden |
IAB20-18 | Hotels and Motels |
IAB7 | Medical Health |
IAB1-5 | Movies |
IAB1-6 | Music |
IAB12 | News and Politics |
IAB13-2 | Personal Finance/ Personal Debt/ Credit Cards |
IAB16 | Pets/ Pet Supplies |
IAB15 | Science |
IAB22 | Shopping/ Children's Games & Toys |
IAB22-2 | Shopping/ Gifts & Greetings Cards |
IAB17 | Sports |
IAB18 | Style & fashion |
IAB18-1 | Beauty |
IAB3-4 | Technology & Computing/ Computing/ Computer Software & Applications |
IAB19 | Technology & Computing/ Consumer Electronics |
IAB19-6 | Smartphones |
IAB9-30 | Video Gaming |