Abstract
A web browsing application can implement a vector database to store session data. A web browsing application can automatically embed loaded web content into an embedded data store that maintains session data for a number of web sessions. A user can query the web browser using simple instructions. The web browser can interpret the instructions and use the embedded data store to quickly search across multiple modalities of embedded data to retrieve relevant results. The web browser can use machine-learned models to answer queries or perform other tasks by performing vector-based queries over the content of visited web data.
Full Text
What is claimed is:
A web browsing application can implement a vector database to store session data. A web browsing application can automatically embed loaded web content into an embedded data store that maintains session data for a number of web sessions. A user can query the web browser using simple instructions. The web browser can interpret the instructions and use the embedded data store to quickly search across multiple modalities of embedded data to retrieve relevant results. The web browser can use machine-learned models to answer queries or perform other tasks by performing vector-based queries over the content of visited web data.
Timeline
Filed
06/11/2026Published
10/01/2026Granted
Not AvailableIPC Codes(3)
G06F 16/9538:Presentation of query results
G06F 16/22:Indexing; Data structures therefor; Storage structures
G06F 16/9535:Search customisation based on user profiles and personalisation