Contextual Font Recommendations based on User Intent
Fuente:
arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866909168390111232 |
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| author | Sharma, Sanat Kumar, Jayant Zheng, Jing King, Tracy Holloway |
| author_facet | Sharma, Sanat Kumar, Jayant Zheng, Jing King, Tracy Holloway |
| contents | 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%. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_08188 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Contextual Font Recommendations based on User Intent Sharma, Sanat Kumar, Jayant Zheng, Jing King, Tracy Holloway Human-Computer Interaction Information Retrieval Machine Learning 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%. |
| title | Contextual Font Recommendations based on User Intent |
| topic | Human-Computer Interaction Information Retrieval Machine Learning |
| url | https://arxiv.org/abs/2306.08188 |