Uber Technologies, Inc.

Google Inc.

Juthika Kiran Dabholkar

Zoltan Gyongyi

Brent Evans Hamby

Darryl DeWeese

Brandon Iles

Albert Segars

Anandsudhakar Kesari

Qun Cao

Yiyuan Xia

Vincent Zammit

Upamanyu Madhow

Kapil Gupta

Dinesh Ramasamy

Jeremy Hintz

William J Salisbury

Roberto Fonti

Anson Chu

Aditya Sarawgi

Houtan Shirani-Mehr

Susmit Biswas

Srihari Reddy

Sai Bhuvan Teja Balla

Moustafa Elshikh

Paul Mahon

Will Salisbury

Zach Song

Brent Hamby

A network system uses Wi-Fi signals or other types of short-range transmissions to determine pickup locations for users receiving services provided via the network system. The network system builds a database of search records mapping pickup locations to signatures of short-range transmission detected by users' client devices when they searched for the pickup locations. By comparing a signature detected by a given user's client device to the signatures in the database, the network system can check for similarities between the short-range transmissions. Responsive to finding a match, the network system predicts that the given user is likely to select a similar pickup location as other users whose client devices detected the signatures corresponding to the match. Accordingly, by leveraging the database, the network system can predict pickup locations without requiring the given user to input a search for a pickup location.

Geographic positioning using short-range transmissions

Methods and apparatus for generating, in response to a search query of a user, a personal search result that identifies a physical location previously interacted with by the user, such as a physical location previously visited by the user. Some implementations are directed to methods and apparatus for determining whether a search query is a personal locational query indicating a desire for information related to one or more physical locations previously interacted with by the user. Some implementations are directed to methods and apparatus for determining search parameters for such a personal locational query. Some implementations are directed to methods and apparatus for searching private content of the user to determine physical locations previously interacted with by the user that are responsive to such a personal locational query. Some implementations are directed to methods and apparatus for generating personal search results that identify determined physical locations previously interacted with by the user.

Personal search result identifying a physical location previously interacted with by a user

Systems and methods are provided for receiving geographic coordinates for a location, determining a road segment associated with the location based on the geographic coordinates for the location, and determining a plurality of places associated with the road segment associated with the location. The systems and methods further provide for extracting visual data for each of the plurality of places, generating a plurality of feature values based on the visual data for each of the plurality of places, and analyzing the plurality of feature values to generate a visibility score for each of the plurality of places.

Place visibility scoring system

A system anticipates one or more destinations that a user may be interested in requesting. Using parameters such as time of day, day of week, and user device location, the system categorizes users according to current user parameters. Categories, which may be predefined by the system, are organized according to similar destination types. In some embodiments, the system determines variety scores indicative of whether a user is likely to select a destination that the user has requested before or more likely to select a new destination, within a selected category. The system uses the determined categories and variety scores to select a list of destinations to suggest to the user.

Recommending destinations of map-related requests using categorization

Systems and methods are provided for receiving geographic coordinates for a location, generating a plurality of candidate places located within a predetermined distance from the location based on the geographic coordinates of the location, and extracting a plurality of features from each candidate place of the plurality of candidate places. The systems and methods are further provided for generating a place score for each candidate place of the plurality of candidate places using the plurality of features for each candidate place of the plurality of candidate places, determining the best candidate place based on the place score for each candidate place of the plurality of candidate places, and providing a place name associated with the best candidate place.

Reverse geocoding system

A travel coordination system identifies geographic locations responsive to a location search request. The geographic locations are organized into a plurality of hierarchical geohash levels, each geohash level mapping the geographic location into a geohash of a different area. The locations search request designates a search context for the search, such as whether the user is searching for an origin of a trip or a destination. The context of the search can be used to determine a geohash level for selecting candidate search results. The candidate search results may be scored based on the context using prior user selections and trips scheduled with the trip coordination system. A geohash and context associated with the user's request may be used to modify a scoring function of the candidate search results based on prior trips.

Contextual search for location services

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San Francisco, CA, United States of America

Juthika Kiran Dabholkar