Bradford B Miller

US Patent:

7365651, Apr 29, 2008

Filed:

Aug 20, 2002

Appl. No.:

10/223979

Inventors:

Noel Massey - Carpentersville IL, US
Robert Gardner - Gilbert AZ, US
Bradford Miller - Austin TX, US

Assignee:

Motorola, Inc. - Schaumburg IL

International Classification:

G08G 1/09

US Classification:

340905, 340990, 701 1

Abstract:

A controller () senses via one or more sensors () parameters that correspond to likely cognitive loading for the driver of a vehicle. Based upon a sense of this cognitive loading, the controller () selects a particular user interface mode from amongst a plurality of user interface modes when receiving a message via a wireless unit () intended for the driver of the vehicle. In general, the selected user interface will present a corresponding cognitive challenge that is reasonable in view of the present cognitive load being experienced by the driver. In one embodiment, the sensor information can be used to also estimate the likely duration of present cognitive loading. This window-of-opportunity information is then additionally used to select a particular user interface option.

US Patent:

20020078090, Jun 20, 2002

Filed:

Jun 29, 2001

Appl. No.:

09/895799

Inventors:

Chung Hwang - Austin TX, US
Bradford Miller - Austin TX, US
Marek Rusinkiewicz - Austin TX, US

International Classification:

G06F015/00

US Classification:

707/513000

Abstract:

A method and system for constructing a text summarization. At least one domain ontology that includes a set of concepts is selected. A user profile indicative of a user's interests is defined in terms of the ontology concepts. A document's relevance to the user is determined based upon the user profile. If the document is relevant, at least a portion of the ontology is used to extract concepts from the document. The degree of match between the extracted concepts and the user profile concepts is determined and the document text summary is generated if the degree of match exceeds a predetermined threshold. Generating the summary may include selecting sentences based on the concepts in the user profile, ranking the selected sentences by relevance to the user profile, selecting sentences for inclusion in the document text summary based upon the ranking, and merging the selected sentences into the document text summary.