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Description

Komprehend AI offers an extensive range of document classification and NLP APIs designed specifically for software developers. Our advanced NLP models leverage a vast dataset of over a billion documents, achieving top-notch accuracy in various common NLP applications, including sentiment analysis and emotion detection. Explore our free demo today to experience the effectiveness of our Text Analysis API firsthand. It consistently delivers high accuracy in real-world scenarios, extracting valuable insights from open-ended text data. Compatible with a wide range of industries, from finance to healthcare, it also supports private cloud implementations using Docker containers or on-premise deployments, ensuring your data remains secure. By adhering to GDPR compliance guidelines meticulously, we prioritize the protection of your information. Gain insights into the social sentiment surrounding your brand, product, or service by actively monitoring online discussions. Sentiment analysis involves the contextual examination of text to identify and extract subjective insights from the material, thereby enhancing your understanding of audience perceptions. Additionally, our tools allow for seamless integration into existing workflows, making it easier for developers to harness the power of NLP.

Description

Text analysis with viztext 2D and 3D mapping text analysis topic modelling, sentiment analysis, wordcloud. Unique machine learning algorithm that visualizes topics in the text you are trying to find. Text analysis allows topic modeling with navigation through 2D/3D maps. This framework uses referential features to create logical relational topic analyses using zoom-in/zoom-out features on 2D/ 3D maps, including colorful word clouds. Analyzes the sentiment level in the text using a pie chart that shows the ratio of positive, neutral and negative. Graphs highlight the top entities in the text by displaying percentages and highlights. Drag and drop, upload text files or paste text from social media posts. Or enter the HTTP address to find a website that contains the text article you wish to analyze.