Palo Alto Research Center Inc.

Google Inc.

Rowan Nairn

Ed H Chi

Lester D Nelson

Victoria M Bellotti

Bongwon Suh

Paul Brian Moody

Philipp Helmut Schmaelzle

Stephen Paul Farrell

Jilin Chen

The disclosure includes a system and method for providing an association recommendation to a user. The system includes a processor and a memory storing instructions that when executed cause the system to: receive a request to disassociate with a first topic from a first user; identify one or more labels and one or more refined topics associated with the first topic; determine a second user that shares one or more second topics in common with the first user; retrieve social graph data describing a social graph associated with the second user; and determine, based on the social graph data associated with the second user, an association recommendation relevant to the first user from the one or more labels and the one or more refined topics.

Providing association recommendations to users

A system and method for content-based message distribution are provided. An incoming message with a recipient address and a tag address including at least one content tag associated with one or more users is received. The content tag within the tag address and a recipient associated with the recipient address are identified. The recipient is added to the content tag as one of the users. The incoming message is displayed to at least one of the users associated with the content tag.

System and method for content-based message distribution

A system including a plurality of pixels disposed on a substrate forming a screen. A signal, such as an image, can be projected on the screen. The pixels of the screen include a sensor configured to sense a portion of the signal, an emitter, and circuitry. In response to information sensed in the signal, the circuitry can be configured to drive the emitter.

Projection system and components

A system and method for recommending interesting content is provided. A content profile including a vector of words extracted from messages associated with a user is obtained. One or more content pointer profiles each including a vector of words associated with a content pointer located within one or more messages are obtained. The content profile is compared with each of the content pointer profiles. A relevance score is determined for that content pointer by calculating a similarity between the user words and the content pointer words. The content pointers are ranked based on the relevance score. A threshold is applied to select the content pointers and those content pointers that satisfy the threshold are selected as the content pointers most relevant to the user.

Recommending interesting content using messages containing URLs

A system and method for content tagging and distribution through email are provided. A user-to-tag record including content tags, each associated with one or more users, is maintained. An incoming email message with a tag address is received. The tag address is processed to identify a content tag, which is applied to the user-to-tag record. Users associated with the identified content tag are determined. The incoming email message is provided to the associated users.

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San Francisco, CA, United States of America

Rowan Nairn