Ebay, Incorporated

Paypal, Inc.

John Roper

Sanjay Pundlkrao Ghatare

Naren M Chittar

Ryan McDonald

Michael Schmitz

Dane Glasgow

Richard Dean Henderson

Sandip Namdeo Gaikwad

A system and method, which may be an offline method, extracts relevant image features about listing items in a network-based publication system for enabling image similarity searching of such listing items. When a seller lists an item, an image of the item is uploaded and may be sent to a picture processing service, which generates several digests. The digests are compressed data structures each representing a particular image feature such as edge, color, texture, or words. These digests are then stored in a search database, where the digests can be used to retrieve listings by image similarity at scale. A similar process can be performed for a query listing for searching the search database for items similar to the query listing.

Finding products that are similar to a product selected from a plurality of products

A system and method extracts relevant image features about listed products in a network-based publication system for enabling image similarity searching of such listed products. When a seller lists a product, an image of the product is uploaded and may be sent to a picture processing service, which generates several digests. The digests are compressed data structures each representing a particular image feature of a listed product such as edge, color, texture, or words. These digests are then stored in a database, where the digests can be used to retrieve listings of products by image similarity at scale. A similar process can be performed for a query by image similarity searching the database for products similar to the query. When a product is located by image similarity search, a selectable icon is provided to enable more products like the located product to be located by image similarity search.

A method and system for removing chrome from a web page is provided. An example system includes a parsing module, a text density analyzer, a content node selector, and a text extractor. The parsing module may be configured to parse a web page into a tree structure. The text density analyzer may be configured to determine a text density score value for each node from the tree structure. The content node selector may be configured to identify one or more nodes from the tree structure as content nodes based on their respective text density score values. The text extractor may be configured to extract text from the content nodes only.

Removing non-substantive content from a web page by removing its text-sparse nodes and removing high-frequency sentences of its text-dense nodes using sentence hash value frequency across a web page collection

Using a processor, receiving, a query including a query image. A database is searched for a set of images similar to the query image, using a two-pass search. The results of the searching are then provided, the results including image members of the set of images similar to the query image. The first pass may be performed using a TF-IDF algorithm and the second pass ranks a predetermined number of results from the first pass by a best match algorithm or other type of algorithm. The type of second pass algorithm may be selectable by a user. If an end signal is not detected, a further two-pass search may be made based on a subsequent query having a subsequent query image. The subsequent query image may be one of the results of the previous two pass search. A subsequent query image may change from an image of a product of a first product category to an image of a product of a second product category.

Searching for more products like a specified product

A system and method, which may be an offline method, extracts relevant image features about images in a network-based publication system for enabling image similarity searching of such images. An image is uploaded and may be sent to a picture processing service, which generates digests. The digests are compressed data structures each representing a particular image feature such as edge, color, texture, or words. These digests are then stored in a search database, where the digests can be used to retrieve images by image similarity at scale. A similar process can be performed for an image query for searching the search database for images similar to the image.

Pre-computing digests for image similarity searching of image-based listings in a network-based publication system

A weighted combination of attributes including but not limited to color, shape, pattern, brand, style, size, and material may be used to rank items when searching for similar items of a given category on an ecommerce system website. The weights on each attribute may be optimized by using feedback from users, the feedback indicating the importance of each attribute to a purchaser when searching for similar items of various categories. Alternatively, click-through patterns from the ecommerce system website can be mined and used to optimize the importance of each attribute to users by item category. The optimum attribute weights for that items category are used to rank the results in a search for similar items in that category.

Growing community of inventors

Sammamish, WA, United States of America

John Roper