Google Inc.

Microsoft Technology Licensing, LLC

Steve Chien

James Aspinall

Mark Yinan Li

Ruwen Hess

Quang Duong

Marc Andreas Schaub

Zhou Bailiang

Frank D Russo

Luuk Van Dijk

Finnegan Southey

Benjamin James Anderson

Paul Donnelly

Dennis Craig Fetterly

Benjamin Ernest Anderson

Nicole S Immorlica

Tong Wang

Li-Sue Chen

Xixi Wang

Ke Xu

The wait time prediction technology determines expected wait times for businesses or other public services using a model generated based on at least historical wait times for the business. In response to a request from a user, an expected wait time for service at the business for at least one particular time period on a particular day of a week is determined using the model and provided for display. User feedback regarding the expected wait time may be requested, and used to refresh the model as new wait times and other information are collected.

Wait time prediction

Presented are techniques of identifying, processing and displaying data point clusters associated with map information in an efficient manner Methods and systems are disclosed which process map information to identify clusters of requested data points for display, based on iterative clustering and filtering of the data points. Methods and systems are also disclosed which generate polygons representing the clusters. The amount of data to be processed and/or displayed can be reduced, without loss of any associated information content in a displayed map.

Identifying, processing and displaying data point clusters

Presented are techniques of identifying, processing and displaying data point clusters associated with map information in an efficient manner. Methods and systems are disclosed which process map information to identify clusters of requested data points for display, based on iterative clustering and filtering of the data points. Methods and systems are also disclosed which generate polygons representing the clusters. The amount of data to be processed and/or displayed can be reduced, without loss of any associated information content in a displayed map.

Real-time busyness information is for a public place is computed in a privacy-sensitive way, and provided for display in relation to historical busyness information. An aggregate amount of real-time location information available for a particular public place is measured (), and used to determine () whether the public place is privacy-qualified. If the public place is privacy-qualified, real-time busyness information is computed () for the public place based on the real-time location information. Further, it is determined () whether the computed real-time busyness information is accuracy-qualified, based on a comparison of the real-time busyness information to historical busyness information. If both qualifications are met, the real-time busyness information is output () for display or to another application.

Realtime busyness for places

Presented are techniques of identifying, processing and displaying data point clusters () associated with map information () in an efficient manner. Methods and systems are disclosed which process map information () to identify clusters () of requested data points for display (), based on iterative clustering and filtering of the data points. Methods and systems are also disclosed which generate polygons (-) representing the clusters. The amount of data to be processed and/or displayed can be reduced, without loss of any associated information content in a displayed map.

A method for static ranking of web documents is disclosed. Search engines are typically configured such that search results having a higher PageRank&#xae; score are listed first. A modified scoring technique is provided whereby the score includes a reset vector that is biased toward web pages linked to blogs. This requires identifying web pages as either blogs or non-blogs.

Ranking method using hyperlinks in blogs

A method for determining semantic correlation between an input query and stored queries based on their temporal correlation. Embodiments include a formal calculation of a correlation coefficient between an input query and stored queries. Alternate embodiments include methods for calculation of a correlation coefficient using a reduced data model and efficient data examination with little or no sacrifice in the accuracy of the correlation coefficient.

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San Carlos, CA, United States of America

Steve Chien