MEDIA & PUBLISHING
Personalization and 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
AI can make the process of searching for products and services on an e-commerce site easier for a user. Most of the time, this convenience is what customers look for in an online retailer as a differentiating factor. AI can recommend us products and help us to get this done by training algorithms to associate products with keywords. It turns the buying process efficient for the customer and drives sales for the business.
An important stage of any person’s life is when he/she decides what career to choose. NLP can be used in building a recommendation system that can evaluate any person’s academic history from documents and recommend career choices. This can be used by career guidance institutions to guide students to choose a career based on their skills, interests and their talents.
Influencer marketing is one of the most effective ways for brands to drive online interactions. Finding an influencer whose persona matches with a brand can be a challenging and tedious process. AI provides a means to automate this process and can be used to efficiently analyze influencers’ content. One solution is to use NLP and semantic analysis to quickly process text content created by the influencers, like post captions, blog submissions, marketing video transcripts to analyze an influencer’s personality, and how well they fit with a brand. The onboarding process becomes less resource-intensive, less time-consuming, and gives an accurate assessment of the influencer’s persona.
Try out these ML models
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Bio-Entity Recognition in Text Blocks
ML for recognizing cells, DNA, and protein types
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