Image-based popularity prediction

• US 10,176,429 B2
• Filed: 02/12/2015
• Issued: 01/08/2019
• Est. Priority Date: 05/24/2011
• Status: Expired due to Fees

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Goswami, Anjan, Chung, Sung Hwan
• Primary Examiner(s): Channavajjala, Srirama
• Application Number:
  US14/621,296
• Publication Number:
  US 20150154503A1
• Time in Patent Office: 1,426 Days
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06F 16/242 Query formulation
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2462 Approximate or statistical queries
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/2471 Distributed queries
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/332 Query formulation
• CPC Class Codes: G06F 16/338 Presentation of query results
• CPC Class Codes: G06F 16/345 Summarisation for human users
• CPC Class Codes: G06F 16/583 using metadata automatically derived from the content
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 16/587 using geographical or spatial information, e.g. location
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06F 18/2115 by evaluating different subsets according to an optimisation criterion, e.g. class separability, forward selection or backward elimination
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06N 5/048 : Fuzzy inferencing
• CPC Class Codes: G06Q 30/02 : Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06V 10/10 : Image acquisition document image scanning and transmission H04N1/00; control of digital cameras H04N23/60
• CPC Class Codes: G06V 10/40 : Extraction of image or video features
• CPC Class Codes: G06V 10/507 : Summing image-intensity values; Histogram projection analysis
• CPC Class Codes: G06V 10/75 : Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
• CPC Class Codes: G06V 10/771 : Feature selection, e.g. selecting representative features from a multi-dimensional feature space
• CPC Class Codes: G06V 20/695 : Preprocessing, e.g. image segmentation

Abstract

Methods and systems for selecting listing based on a click predictions score are disclosed. The server system includes one or more processors, memory, and one or more programs stored in the memory. The server system receives a search query from a client system. In response to receiving the search query, the server system identities a plurality of item listings relevant to the received search query. For each identified item listing, the server system generates a click prediction score, wherein a click predication score represents the estimated likelihood that a user will click on the listing. The server system ranks the plurality of item listings based on the generated click prediction score and selects a predetermined number of the item listings for transmission to the client system based on their ranking and associated click prediction score. The server system transmits one or more item listings to the client system for display.

Claims

1. A system comprising:

one or more processors;

memory; and

one or more programs stored in the memory, the one or more programs comprising instructions that cause the one or more processors to perform operations comprising;

receiving a search query from a client system;

in response to receiving the search query, identifying a plurality of item listings relevant to the received search query, the plurality of item listings including at least a first item listing that comprises an image that includes image features, the image features including image dimensions;

generating a bounding box based on the image dimensions of the image;

computing a distribution of pixel colors located outside of the bounding box;

identifying a foreground of the image based on the distribution of pixel colors located outside of the bounding box;

segmenting the image into a foreground area and a background area based on the identifying the foreground of the image based on the distribution of pixel colors;

extracting color pixel values from the foreground area of the image;

generating a color histogram based on the color pixel values extracted from the foreground of the image;

generating an image quality score of the image of the first item listing based on the color histogram and a ratio of the foreground area and the background area;

ranking the first item listing among the plurality of item listings based on the image quality score; and

communicating for display of a presentation of the plurality of item listings at the client system, the presentation of the plurality of item listings including the first item listing at a position among the plurality of item listings, the position based on the ranking of the first item listing.

2. The system of claim 1, wherein the instructions cause the system to perform operations further comprising:

storing historical click data for the first item listing; and

ranking the first item listing among the plurality of item listings based on the image quality score and the historical click data.

3. A method comprising:

receiving a search query from a client system;

in response to receiving the search query, identifying a plurality of item listings relevant to the received search query, the plurality of item listings including at least a first item listing that comprises an image that includes image features, the image features including image dimensions;

generating a bounding box based on the image dimensions of the image;

computing a distribution of pixel colors located outside of the bounding box;

identifying a foreground of the image based on the distribution of pixel colors located outside of the bounding box;

segmenting the image into a foreground area and a background area based on the identifying the foreground of the image based on the distribution of pixel colors;

extracting color pixel values from the foreground area of the image;

generating a color histogram based on the color pixel values extracted from the foreground area of the image;

generating an image quality score of the image of the first item listing based on the color histogram and a ratio of the foreground area and the background area;

ranking the first item listing among the plurality of item listings based on the image quality score; and

communicating for display of a presentation of the plurality of item listings at the client system, the presentation of the plurality of item listings including the first item listing at a position among the plurality of item listings, the position based on the ranking of the first item listing.

4. The method of claim 3, wherein the method further comprises:

storing historical click data for the first item listing; and

ranking the first item listing among the plurality of item listings based on the image quality score and the historical click data.

5. A non-transitory machine readable storage medium storing instructions, that when executed by one or more processors, causes the one or more processors to perform operations comprising:

receiving a search query from a client system;

in response to receiving the search query, identifying a plurality of item listings relevant to the received search query, the plurality of item listings including at least a first item listing that comprises an image that includes image features, the image features including image dimensions;

generating a bounding box based on the image dimensions of the image;

computing a distribution of pixel colors located outside of the bounding box;

identifying a foreground of the image based on the distribution of pixel colors located outside of the bounding box;

segmenting the image into a foreground area and a background area based on the identifying the foreground of the image based on the distribution of pixel colors;

extracting color pixel values from the foreground area of the image;

generating a color histogram based on the color pixel values extracted from the foreground area of the image;

generating an image quality score of the image of the first item listing based on the color histogram and a ratio of the foreground area and the background area;

ranking the first item listing among the plurality of item listings based on the image quality score; and

communicating for display of a presentation of the plurality of item listings at the client system, the presentation of the plurality of item listings including the first item listing at a position among the plurality of item listings, the position based on the ranking of the first item listing.

6. The non-transitory machine readable storage medium of claim 5, wherein the instructions cause the machine to perform operations further comprising:

storing historical click data for the first item listing; and

ranking the first item listing among the plurality of item listings based on the image quality score and the historical click data.