Contextual Font Recommendations based on User Intent
Sanat Sharma, Jayant Kumar, Jing Zheng, Tracy Holloway King

TL;DR
This paper presents a system that recommends fonts based on user intent, enhancing font selection in Adobe Express by considering multilingual input and user entitlements, resulting in over 25% CTR among millions of users.
Contribution
The work introduces a novel intent-driven font recommendation system tailored for Adobe Express, improving user experience with contextual suggestions.
Findings
Over 25% CTR on font recommendations
Supports multilingual text input
Adjusts font suggestions based on user entitlements
Abstract
Adobe Fonts has a rich library of over 20,000 unique fonts that Adobe users utilize for creating graphics, posters, composites etc. Due to the nature of the large library, knowing what font to select can be a daunting task that requires a lot of experience. For most users in Adobe products, especially casual users of Adobe Express, this often means choosing the default font instead of utilizing the rich and diverse fonts available. In this work, we create an intent-driven system to provide contextual font recommendations to users to aid in their creative journey. Our system takes in multilingual text input and recommends suitable fonts based on the user's intent. Based on user entitlements, the mix of free and paid fonts is adjusted. The feature is currently used by millions of Adobe Express users with a CTR of >25%.
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Taxonomy
TopicsVideo Analysis and Summarization · Artificial Intelligence in Games · Web Data Mining and Analysis
MethodsLib
