Category: Amazon Comprehend

TINT is a simple, DIY platform that helps brands find, curate, and display their most effective customer-generated content from social media on marketing channels such as websites, mobile apps, and event displays. Businesses can link their Twitter, YouTube, Pinterest, Instagram, Facebook, and RSS feeds to their TINT accounts The social media aggregator uses machine learning […]

Amazon Web Services (AWS) brings image and video analysis, natural language processing, speech recognition, text-to-speech, and machine translation within the reach of every developer. With machine learning (ML) services by AWS, you can plug in prebuilt AI functionality into your apps without having to worry about ML models. Thousands of developers have used Amazon ML […]

We’re excited to announce that Amazon Comprehend now provides a Syntax API.  This enables you to tokenize text (for example, to extract word boundaries) and the corresponding part of speech (PoS) for each word. Today, Amazon Comprehend enables analysis use cases like such as knowing whether a customer comment is negative or positive, and identifying […]

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text.  Starting today, you have the option to analyze a collection of documents stored in an Amazon S3 bucket using our new asynchronous job service. This is in addition to single and multiple document synchronous calls […]

VidMob is a social video creation platform that marketers of all sizes can use to develop personalized advertising communications at scale. VidMob uses machine learning (ML) to power its SaaS application. This application uses metadata extraction and sentiment analysis to provide marketers with actionable insights into which creative assets resonate with their intended audience, and […]

Today consumers are encouraged to express their satisfaction or frustration with a company or product through social media, blogs, and review platforms. Sentiment analysis can help companies better understand their customers’ opinions and needs and make more informed business decisions. Amazon released a dataset to the public with over 130 million product reviews in multiple […]

In this blog post, we will show you how to get started building rich text analytics views from your database, without having to learn anything about machine learning for natural language processing models. We’ll do this by leveraging Amazon Comprehend, paired with Amazon Aurora-MySQL and AWS Lambda.

The demand for chat apps is growing wildly. From social apps to business collaboration, in-game chat to customer support, every app needs chat. Chat apps like Telegram are making mainstream news and generating widespread interest.

Historically, building a scalable, feature-rich chat app was surprisingly difficult. Not anymore. PubNub ChatEngine has integrated Amazon machine learning APIs, which makes building intelligent, scalable chat apps super easy for mobile and web.

In this blog post, you’ll learn how to spin up the PubNub ChatEngine and add Amazon Translate and Amazon Polly for cross-lingual, speech-enabled chat apps that you can embed anywhere.

ClearView Social enables a company’s employees to share approved content on LinkedIn, Twitter, and other social networks with a single click. It then broadcasts the content to those social networks at peak times, and tracks the resulting engagement with a leaderboard and an analytics dashboard. According to Bill Boulden, CTO of ClearView Social, a key […]

In today’s world, public content has never been more relevant. Data from customer reviews is being used as a tool to gain insight into consumption-related decisions as the understanding of its associated sentiment grants businesses invaluable market awareness and the ability to proactively address issues early. Sentiment analysis uses a process to computationally determine whether […]