Media Natural Language Generation is a growing feature. From finance to sports, from politics to millions of individualized stories, our partner Wordsmith is revolutionizing media. Companies like The Associated Press are expanding output by orders of magnitude and freeing up staff time, all while decreasing errors.
Media Natural Language Generation is an essential component of our Retail suite
How does Media Natural Language Generation works? The 4implementation steps are similar to the eCommerce Mash’n Learn process:
1. Establish the automated content strategy
Depending on your goals, we have to build up to 4 different types of published contents: for email Marketing, for Twitter/Facebook, for a printed Journal/Magazine or for Product features.
2. Structuring Data and Contents
Create a Data Warehousing gathering all texts produced for similar contents. Depending on the targeted quality, this process can take a while. The more source content we use, the more human the automated generated articles will be.
3. Build the outputs
From all the content templates, we build a significant number of generated scenarios that will be tested during 2 weeks until all stakeholders agree on the result.
4. Integrate with all interfaces
Our skills at Mash’n Learn are Data Mining and Integration with information systems and publishing tools (HTML, eCommerce platforms, Adobe suite, Social Media). We will your Natural Language Generation robot to be quickly ready to be autonomous.
Media Natural Language Generation: we can help
At Mash’n Learn, we fix your content with Machine Learning
From Natural Language Generation to Predictive Analysis, Mash’n Learn provides a complete tool suite for the large catalog retailers.
For a Media Natural Language Generation project, this is an Alpha implementation planning that target going live within two weeks (assuming all resources are available):
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Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33
