Google iOS App Now Suggest Related Content - Cloud Search Now Using NLP

While viewing a web page a carousel fo related content suggestions appear when you reach the bottom of a webpage. Cloud Search bring the power of NLP to G Suite.

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You can now search and discover releated contents with the Google app for iOS updating today, brings new "suggestions for related content" in an expandable carousel, that appear at the bottom of the page that you are reading on the iOS app.

No matter what you are reading, this new feature is here to make it easier to explore and discover content while browsing the web.

Here is how the feature work? Suppose, you just finished reading an article, and when you start scrolling back up, a carousel of additional articles on the topic will appear. The carousel can be expanded and browsed, and tapping on any of the item will launch a new site or page(s) —say you're reading a recipe for roasting shishito peppers, you'll be able to jump straight to other ways to prepare them, such as grilling them, with a single tap, writes Google.

Alternatively, you can see the GIF animation below showing how it works:

Related content suggestion on Google app for iOS

This feature is currently only available in U.S., but will expand to more locales and languages in near future.

Get the latest version of the Google app for iOS on Apple App Store, to start searching away!

Google Cloud Search, a G Suite tool that leverages machine learning (ML) now let you search more intuitively using natural language processing (NLP).

Just like Google Search, the Cloud Search (formerly known as Springboard) now let you intitiate search queries in everyday language to find information in the workplace, like for example enterprise search queries may start with a "what," "who," "how" or "when."

If you're looking for a Google Doc, now using the intuitive search, you may type questions like "Docs shared by Mary," "Who's Bob's manager?" or "What docs need my attention?" — and Cloud Search will show you answer cards with relevant information.

See this NLP Cloud Search GIF:

google cloud search with nlp

Further, the company notes, more capabilities including integration with third-party applications will be coming to Cloud Search in near future.

Cloud Search, rolls out to all customers using the G Suite Business and Enterprise editions across the world.

Also today, Google has launched two new features to "Cloud Natural Language," including: a new content classifier and entity sentiment that digs into the detail of what a story is actually about.

See another Cloud Searchs’ NLP example in this GIF:

Google Cloud Search using NLP

Automatically classify content

First up, through predefined content classification, CNL now automatically sort documents and content into 700 plus different categories, including Arts & Entertainment, Hobbies & Leisure, Law & Government, News, Health, and more.

With machine learning (ML) now powering Cloud Natural Language, industries like media and publishing can now automatically organize their articles and content more efficiently — unlike traditionally, when they had to manually sort, label and categorize content.

Analyze sentiment of entities

And second, the Sentiment analysis, now offers more granularity with "entity sentiment analysis" —rather than analyzing sentiment of a sentence or block of text, users can now parse the sentiment of places or things, says Google.

Google also highlighted other tools to help its Journalism & News publishers take advantage of machine learning, like:

  • Improve newsroom's efficiency using Google Cloud Vision and Video Intelligence, that tags images and videos based on the content inside the actual image. This metadata can then be used to make it easier and quicker to find the right visual.
  • Engage with new audiences with tools such as, Google Cloud Translation, offers a simple interface to translate content into more than 100 languages. GoogleFish help editors quickly translate existing Vice articles into local language and push them to a local editor of the market.
  • Monetize audience using Cloud Datalab, that help identify new subscription opportunities and offerings. The metadata collected from image, video, and content tagging creates an invaluable dataset to advertisers, such as audiences interested in local events or personal finance, or those who watch videos about cars or travel.
  • Experiment with new formats by using TensorFlow's "summary.text" that help publishers quickly experiment with creating short form content from longer stories. Also, Reddit recently launched a similar "tl;dr bot" that summarizes long posts into digestible snippets.
  • Keep your content safe for toxicity in comments with Jigsaw's Perspective, an API that uses machine learning to spot harmful comments which can be flagged for moderators.