All activity
Semantic Analysis for Hotel Reviews consists of 149 Semantic Models.
Each Semantic Model was especially designed, built, tested, and re-tested on hundreds of thousands of hotel reviews from 10 different sources.
149 Semantic Models for Hotel ReviewsExplainable&Debuggable AI at a cost of automation.
Hate Speech Detection for User-Generated Content is a set of dedicated semantic models regarding toxic and aggressive content. It was made on a various type of user-generated content (comments, forums, tweets, fb, etc.).
Hate Speech DetectionHate Speech Detection for User-generated Content.
Sentiment Analysis 2.0 for App Reviews is a set of precisely crafted 74 semantic models especially for app reviews.
Contact us to get more information about custom-made models tailored to your data&requirements.
74 Semantic Models for App ReviewsSentiment Analysis 2.0 for App Reviews.
Profanity & Toxicity Detection for User-Generated Content is a set of dedicated semantic models regarding toxic and aggressive content. It was made on a various type of user-generated content (comments, forums, tweets, fb, etc.).
Profanity & Toxicity DetectionProfanity & toxicity detection for user-generated content
Tom Krupaleft a comment
You can use the publically available version on RapidAPI (https://rapidapi.com/unicornNLP/api/profanity-toxicity-detection-for-user-generated-content), or Contact Us to get more information about custom-made products tailored to your requirements and to your type of texts.
Profanity & Toxicity DetectionProfanity & toxicity detection for user-generated content
Sentiment Analysis 2.0 for Hotel Reviews consists of 149 Semantic Models. Each Semantic model was especially designed, built, tested, and on hundreds of thousands of reviews. All presented Semantic Models work with an unparalleled precision of 90-95%.
Sentiment Analysis 2.0 for Hotel ReviewsHuman-like quality at the cost of automation