Google Inc.

Melanie Clements

Andrea Lynn Frome

Baris Yuksel

Ethan G Russell

Douglas Richard Grundman

Paul Eastlund

Diego Ariel Gertzenstein

Howard Wellington Trickey

Systems and methods are provided for determining whether given business listings are spam or are closed businesses. In one example, a system receives a business listing from a user. The business listing contains a geolocation and the name of a business. The system also receives one or more street level images related to a geographic object that is at or near the same geolocation as the business listing. The system determines if the business listing is spam or is closed based on the received street level images by determining if the geographic object is the business or by analyzing whether the business associated with the listing is shown in any of the street level images.

Systems and methods of correlating business information to determine spam, closed businesses, and ranking signals

The present invention relates generally to identifying incorrect or fraudulent business listings. More specifically, business listings may be validated by comparing the listing information to information identified from images at or near the location of the business. For example, a plurality of geolocated street level images of various locations may be categorized using computer vision techniques. A particular business listing may include, among other information, a location (address, etc.) as well as a business category. The pre-categorized images are then selected based on the location of the particular business listing. The categories of the selected images are then compared to the category of the particular business listing to validate the business listing.

Using images to identify incorrect or invalid business listings

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Jersey City, NJ, United States of America

Melanie Clements