The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Apr. 15, 2014
Filed:
Apr. 04, 2008
Susan T. Dumais, Kirkland, WA (US);
William H. Gates, Iii, Medina, WA (US);
Srikanth Shoroff, Sammamish, WA (US);
Michael Ehrenberg, Seattle, WA (US);
Jensen M. Harris, Bellevue, WA (US);
Richard J. Wolf, Seattle, WA (US);
Joshua T. Goodman, Redmond, WA (US);
Eran Megiddo, Bellevue, WA (US);
Susan T. Dumais, Kirkland, WA (US);
William H. Gates, III, Medina, WA (US);
Srikanth Shoroff, Sammamish, WA (US);
Michael Ehrenberg, Seattle, WA (US);
Jensen M. Harris, Bellevue, WA (US);
Richard J. Wolf, Seattle, WA (US);
Joshua T. Goodman, Redmond, WA (US);
Eran Megiddo, Bellevue, WA (US);
Microsoft Corporation, Redmond, WA (US);
Abstract
Providing for generation of a task oriented data structure that can correlate natural language descriptions of computer related tasks to application level commands and functions is described herein. By way of example, a system can include an activity translation component that can receive a natural language description of an application level task. Furthermore, the system can include a language modeling component that can generate the data structure based on an association between the description of the task and at least one application level command utilized in executing the computer related task. Once generated, the data structure can be utilized to automate computer related tasks by input of a human centric description of those tasks. According to further embodiments, machine learning can be employed to train classifiers and heuristic models to optimize task/description relationships and/or tailor such relationships to the needs of particular users.