This is a Plain English Papers summary of a research paper called First Cross-App Multimodal Search Dataset Shows How Users Navigate Mobile Apps. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Overview
- Qilin dataset contains 8.4 million multimodal search sessions from real mobile app usage
- Features interactions across 9 different mobile apps with diverse content types
- Includes text, image, and hybrid search queries with corresponding search results
- First dataset to track user behaviors across multiple apps in sequence
- Contains 2.2 million unique images and 6.9 million text documents
- Enables research on how users navigate between different mobile applications
Plain English Explanation
The Qilin dataset is like a digital diary of how people actually search for information on their phones. Instead of just tracking what people search for on a single app like Google, it follows users as they hop between different apps like news readers, social media, e-commerce ...
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