Media and Publication industry is going through a revolutionary change with AI and ML stepping into the shoes of the writers and editors. With the explosion of the information age and the advent of platforms such as Wikipedia, Wattpad, YouTube, Spotify, Netflix, etc, the industry is changing at an unprecedented rate. The creation and consumption of content happens round the clock with billions around the world reading, writing, watching and listening to both online and offline media. Hence, it is the need of the hour for Media and Publishing industry to change the traditional ways of creation, curation, and publication of content and embrace the immense possibilities of Artificial Intelligence and Machine Learning.
NATURAL LANGUAGE PROCESSING - Personalization and Recommendation
Personalization & Recommendation
Breakthroughs in the field of AI and ML are helping the media houses to personalize the content that appeals to the mass population. Personalization also helps recommend the right content to the right target audience such as in the case of a news briefing by Google News or suggestions on what to read on Kindle e-reader based on the users’ past readings and interests
NATURAL LANGUAGE PROCESSING - Categorization
The age of the internet has brought with its troves of content and data which has become impossible to categorize manually. ML helps companies to automate this process by training algorithms which can categorize a huge amount of text, image, audio, video content into predefined categories and topics
NATURAL LANGUAGE PROCESSING - Content Moderation
User-generated content can have elements which can be inappropriate to certain users of the media. Strict regulations have also made it mandatory for publishers to moderate the content on their platforms. ML can help in this regard by screening the posts and content in real-time to adhere to the policy and standards
NATURAL LANGUAGE PROCESSING - Sentiment Analysis
Sentiment Analysis and Tagging
Identifying the sentiments and preferences of your audience helps creators in curating the next content in a way that will appeal to the customers. AI helps in identifying these sentiments from a large base of feedback, reviews, and comments (even likes and dislikes) and tag the reactions using ML
COMPUTER VISION - Image Verificationn & Quality Control
“You Can't Judge a Book by the Cover” has been replaced by “A cover should give a sneak peek into the book”. More so in the times when not just books, but music, film, blogs, articles, posts, etc are all vying for the customer’s attention. The thumbnail selection tool integrated into the AI product can analyze the content and predict the best thumbnails such as a cover for a book, poster for films and music, thumbnails for online media, etc
Try out these ML models
Q&A Topic Tags
Tag user-provided topics from Q&A sessions
Advertisement Sentiment Analysis
Understanding ads sentiment and topics
AI-assisted watermark detection from images using computer vision
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