Google Inc.

Kathryn Rose Vanderwater

Frances Bordwell Haugen

Alexander Ketner Unger

In one aspect, a method includes identifying one or more contacts associated with a user at one or more social networking services, identifying one or more social content items associated with the one or more contacts, generating one or more of candidate suggestions from the one or more social content items, the one or more candidate suggestions including n-grams generated from the one or more social content items, wherein each n-gram comprises a string of characters, ranking the one or more candidate suggestions according to one or more significance criteria and selecting one or more suggestions of the plurality of candidate suggestions according to the ranking. Other aspects can be embodied in corresponding systems and apparatus, including computer program products. These and other aspects can include one or more of the following features.

Providing suggestions to a user based on social activity patterns

Methods for ranking users based on contextual factors are provided. An example method may include receiving an online question by an asking user. The method may further include identifying one or more topics of the received online question. The method may further include identifying a set of candidate answering users from a plurality of users based on an expertise level of each user of the plurality of users, wherein the expertise level is related to the identified one or more topics of the received online question. In addition, the method may include ranking the set of candidate answering users based on a commonality of one or more contextual factors between the asking user and the set of candidate answering users, wherein the one or more contextual factors are distinct from the identified one or more topics. Systems and computer-readable media for ranking users based on contextual factors are also described.

Ranking users based on contextual factors

Methods relating to canonical content items are provided. An example method may include receiving an online question by an asking user. The method may further include identifying one or more topics of the received online question. The method may further include matching at least one canonical content item from a plurality of canonical content items to the received online question based on the identified one or more topics, wherein each canonical content item of the plurality of canonical content items is associated with a model explanation of a topic. In addition, the method may include providing the matched at least one canonical content item to the asking user. Systems and computer-readable media are also described.

Identifying canonical content items for answering online questions

The subject technology determines population density of an area in order to map one or more persons to smaller areas such as bathrooms, stores, and lines. Based on a user's current geolocation, the subject technology utilizes one or more nearby wireless signals transmitted from computing devices to determine a population density of an area near the user's geolocation. The signals from each device can include unique IDs for identifying the device associated with the ID. Mobile devices such as cell phones constantly broadcast a cell signal and/or other types of signals with unique identifiers. These signals are anonymized to protect any personal information associated with the mobile devices transmitting these signals while still being able associate a device to a respective signal. The subject technology therefore can determine an area's population density based on these anonymized signals by detecting one or more associated devices near the geolocation of the user.

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Plainfield, IL, United States of America

Kathryn Rose Vanderwater