Text Moderator - TEMOthy

Intelligently detect potential profanity in more than 100 languages checks for possible PII instantly in your text.

This will help you detect potential profanity in more than 100 languages and match text against your custom lists automatically. Text Moderator activity also checks for possible personally identifiable information (PII).

• Detect potential profanity in text with term-based filtering

> If the API detects any profane terms in any of the supported languages, those terms are included in the response. The response also contains their location (Index) in the original text. The ListId in the following sample JSON refers to terms found in custom term lists if available.

> Content Moderator’s machine-assisted text classification feature supports English only, and helps detect potentially undesired content. The flagged content may be assessed as inappropriate depending on context. It conveys the likelihood of each category and may recommend a human review. The feature uses a trained model to identify possible abusive, derogatory or discriminatory language. This includes slang, abbreviated words, offensive, and intentionally misspelled words for review.

• Use machine-learning-based models to classify the text into three categories.
• Detect personally identifiable information (PII) such as US and UK phone numbers, email addresses, and US mailing addresses.

> The PII feature detects the potential presence of this information:

> Email address US Mailing address IP address US Phone number UK Phone number Social Security Number (SSN)

• Normalize text and autocorrect typos
• If you ask for auto-correction, the response contains the corrected version of the text:

With workflows infused with this capability, one would be able to block, approve or review the content based on policies and thresholds in the orgnization in a more intelligent and automated fashion. This can augment and future-proof security procedures utilizing advance cognitive technologies that can be also customized according to the company's needs, thru active learning.