摘要:
The present invention is a computer-enabled method for combining information stored in a hierarchical classification structure, such as the International Patent Classification system, with the frequency of events resulting from human decision processes in order to generate an association index for a patent classification. The association index can then be used to quickly analyze a portfolio of patents.
摘要:
As computer programs grow more complex, extensible, and connected, it becomes increasingly difficult for users to understand what has changed on their machines and what impact those changes have. An embodiment of the invention is described via a software tool, called AskStrider, that answers those questions by correlating volatile process information with persistent-state context information and change history. AskStrider scans a system for active components, matches them against a change log to identify recently updated and hence more interesting state, and searches for context information to help users understand the changes. Several real-world cases are provided to demonstrate the effectiveness of using AskStrider to quickly identify the presence of unwanted software, to determine if a software patch is potentially breaking an application, and to detect lingering components left over from an unclean uninstallation.
摘要:
The present invention is a computer-enabled method for combining information stored in a hierarchical classification structure, such as the International Patent Classification system, with the frequency of events resulting from human decision processes in order to generate an association index for a patent classification. The association index can then be used to quickly analyze a portfolio of patents.