Google Inc.

Blue Kai, Inc.

Charles Yang

Charles Joseph Rosenberg

Louis Wang

John Patrick Connelly

Lucian Vlad Lita

Michael David Bigby

The subject matter of this specification generally relates to providing content related to text depicted in images. In one aspect, a system includes a data processing apparatus configured to extract text from an image. The extracted text is partitioned into multiple blocks. The multiple blocks are presented as respective first user-selectable targets on a user interface at a first zoom level. A user selection of a first block of the multiple blocks is detected. In response to detecting the user selection of the first block, portions of the extracted text in the first block are presented as respective second user-selectable targets on the user interface at a second zoom level greater than the first zoom level. In response to detecting a user selection of a portion of the extracted text within the first block, an action is initiated based on content of the user-selected text.

Efficiently augmenting images with related content

The subject matter of this specification generally relates to providing content related to text depicted in images. In one aspect, a system includes a data processing apparatus configured to extract text from an image. The extracted text is partitioned into multiple blocks. The multiple blocks are presented as respective first user-selectable targets on a user interface at a first zoom level. A re user selection of a first block of the multiple blocks is detected. In response to detecting the user selection of the first block, portions of the extracted text in the first block are presented as respective second user-selectable targets on the user interface at a second zoom level greater than the first zoom level. In response to detecting a user selection of a portion of the extracted text within the first block, an action is initiated based on content of the user-selected text.

A system, method, apparatus and processor readable media are described for real-time prediction of an advertising audience volume through analysis of historical audience data, and tuning of the predicted audience volume. Embodiments enable a user to specify a query for audience volume prediction. Such a query may be a Boolean combination of various audience categories. A time range may be determined that indicates the amount of historical data that is to be analyzed to make the audience volume prediction in real time. Employing the user-specified query, an audience volume prediction may be provided for a future time period, based on an analysis of retrieved historical audience data for the time range. Embodiments may also enable a user to tune the predicted audience volume through modification of the query through one or more iterations.

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Fremont, CA, United States of America

Charles Yang