HCIRLGJun 14, 2023

Contextual Font Recommendations based on User Intent

arXiv:2306.08188v12 citationsh-index: 29
Originality Incremental advance
AI Analysis

This solves the font selection challenge for Adobe Express users, particularly casual ones, by offering personalized recommendations to enhance creativity.

The paper tackles the problem of font selection from a large library by creating an intent-driven system that provides contextual font recommendations based on user input, resulting in a click-through rate of over 25% for millions of users.

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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