Abstract: Techniques for determining a set of keywords associated with a document are provided. A document is received that may be classified into a taxonomy that includes a plurality of categories. A categorization ranking is determined for each category for the received document. A set of categories of the taxonomy having highest categorization rankings is determined for the received document. Documents representing the set of categories having highest categorization rankings are combined together into a cumulative representative text that includes a plurality of terms. A cumulative term corpus importance score is determined for each term in the cumulative representative text. The cumulative term corpus importance score for a particular term indicates an importance of the particular term in a context of the cumulative representative text. A set of terms of the cumulative representative text having highest cumulative term corpus importance scores is selected to be keywords for the received document.

Abstract: Techniques for determining a set of keywords associated with a document are provided. A document is received that may be classified into a taxonomy that includes a plurality of categories. A categorization ranking is determined for each category for the received document. A set of categories of the taxonomy having highest categorization rankings is determined for the received document. Documents representing the set of categories having highest categorization rankings are combined together into a cumulative representative text that includes a plurality of terms. A cumulative term corpus importance score is determined for each term in the cumulative representative text. The cumulative term corpus importance score for a particular term indicates an importance of the particular term in a context of the cumulative representative text. A set of terms of the cumulative representative text having highest cumulative term corpus importance scores is selected to be keywords for the received document.

Abstract: A document may be classified by traversing a hierarchical classification tree and comparing the words in the document to words in documents representing the nodes on the classification tree. The document may be classified by traversing the classification tree and generating a comparison score based on word comparisons. The score may be used to trim the classification tree or to advance to another node on the tree. The score may be based on a scarcity or importance of individual words in the document compared to the scarcity or importance of words in the category. The result may be a set of classifications with scores for those classifications.

Abstract: Methods, systems, and computer-readable media are disclosed for operating system-based application recovery. A particular method saves an application state of an application executing at a computer. When a failure of the application is detected, the operating system provides an option to initiate recovery of the application by reverting to the saved application state. When the option to initiate recovery is selected by a user of the computer, the operating system recovers the application by reverting to the saved application state.

Abstract: Methods, systems, and computer-readable media are disclosed for operating system-based application recovery. A particular method saves an application state of an application executing at a computer. When a failure of the application is detected, the operating system provides an option to initiate recovery of the application by reverting to the saved application state. When the option to initiate recovery is selected by a user of the computer, the operating system recovers the application by reverting to the saved application state.