Best Practices Guide
This short presentation, 9 slides – attached PDF, is a key reference for anyone using IBM’s Watson Natural Language Classifier service. Whether you’re classifying risky investments or sorting product descriptions, these tips are essential for any developer using the API.
Don’t believe me? Check it out yourself: IBM Watson Natural Language Classifier Best Practices Guide
Here are some examples to help you start thinking of what to try next with Watson Natural Language Classifier:
- E-commerce and Retail: Tag products or identify fraudulent items. Think of all those product descriptions or user reviews you see, help your users choose products by narrowing the choices by theme.
- Higher Education and Government: Sort text or documents into categories. Academia, law, non-profit organizations, all have some form of classification. Put Watson to the test.
- Social Media: Tweets, Emails, Posts, and Shares are the new mail. Analyze and sort them into categories. From identifying content to civic issues, THINK outside the box with social media.
- Services: Support tickets, service queries, and messages can be difficult to parse. Use Watson to categorize customer issues and provide faster solutions.
- Talent Solutions: Analyze resumés and applications to derive deeper meaning and soft skills.