How Software Automatically Collects and Organizes Data from Multiple Websites
A system that automatically logs into multiple websites, pulls information, and stores it locally before you even ask for it, so it is ready to view instantly.
Patent Number
US 8112476
Status
Active
Filing Date
April 4, 2011
Grant Date
February 7, 2012
Expiration
~April 2031 (estimated)
Claims
62
Assignee
Confluence Commons Inc
Inventors
Michael C. Wilson, Michael D. McMahon, Chris Young, Andrew Hartman, Jared Polis, Peter K. Trzyna, Scott Shaver, Eric Wu, Payal Goyal, Samuel C. Wu, David L. Calone, Andrew Hyde, Jeffery D. Herman
Citations
18 forward · 22 backward
What it covers
The patent describes a software-based aggregation system that acts as a middleman between a user's computer and various third-party websites. The system automatically authenticates (logs in) to multiple sites, retrieves data from them, and parses that data into a unified display. A key feature is the 'look ahead' mechanism, where the system caches information in the local memory of the user's computer based on an anticipated request. For example, if you use a dashboard that aggregates your email, social media, and news, this system pre-fetches and stores that data locally so it appears immediately when you open the application.
What it doesn't cover
- —Does not cover server-side aggregation where the data is collected and processed on a remote server before being sent to the user.
- —Does not cover aggregation methods that do not use local caching based on anticipated requests.
- —Does not cover systems that lack an automated authentication mechanism for the third-party sites.
The clever bit
The innovation lies in moving the 'look ahead' caching logic to the client-side (the user's computer) rather than the server, allowing the system to be platform-independent and faster by reducing latency for the end user.
Why it matters
This patent addresses the challenge of managing fragmented information across the early web, such as disparate email accounts, social networks, and job boards. By moving the heavy lifting of authentication and data retrieval to the client-side and using predictive caching, it aimed to create a faster, more integrated user experience for desktop-based dashboard applications.
Real-world examples
- 1.Personalized news and social media dashboards
- 2.Unified email clients that pull from multiple providers
- 3.Job search aggregators
- 4.Multi-platform instant messaging clients
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US 8112476 · 2026