How Search Engines Rank Images Using User Ratings
A system that improves image search results by combining how well an image matches a search term with how highly users have rated that image elsewhere.
Original patent title: “Ranking content based on relevance and quality”
A system that improves image search results by combining how well an image matches a search term with how highly users have rated that image elsewhere. Granted to Microsoft Corp in 2010 with 9 claims and 46 forward citations.
Key facts
Coverage
What does this patent actually cover?
This system improves search results by calculating a final score for images based on two distinct factors. First, it measures relevance by comparing search keywords to metadata associated with the image. Second, it calculates a quality score based on user ratings from various image forums, which is determined before any search query occurs. The system normalizes these ratings across different forums to ensure a five-star rating on one site is comparable to a ten-point scale on another. Finally, it combines these two scores to re-rank the search results, ensuring high-quality images appear higher than low-quality ones even if their relevance to the search term is identical.
The gap
What does this patent NOT cover?
- Does not cover ranking systems that rely solely on keyword matching without incorporating external user ratings.
- Does not cover real-time ranking adjustments based on user clicks or behavioral data collected during the search session.
- Does not cover ranking methods that fail to normalize ratings across different platforms.
- Does not cover systems that lack a pre-calculated quality score independent of the specific search query.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
What made this novel
The system treats the 'quality' of an image as a static, pre-calculated property that is independent of the search query, allowing the engine to mathematically merge objective quality with subjective relevance.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Google Image Search results
Bing Image Search
Pinterest search ranking
Stock photo site search algorithms
Why it matters
The bigger picture
This patent addresses the fundamental problem of search engine 'spam' and low-quality results. By shifting the focus from simple text matching to incorporating community-driven quality metrics, it helped search engines provide more useful results. It reflects the transition of the web from a static collection of pages to a social, community-rated ecosystem.
Filed
January 25, 2006
Granted
November 16, 2010
Market context
Who's building on this
Companies in this space
Microsoft continues to integrate these ranking principles into Bing. Major search providers like Google and platforms like Pinterest have built upon these concepts, evolving them into more complex machine learning models that incorporate user engagement and visual analysis.
Market impact
This approach helped standardize the use of crowd-sourced metadata in search algorithms. It moved the industry away from purely keyword-based search toward quality-aware retrieval, which is now a standard requirement for any modern search engine or content discovery platform.
Claim 1 — Plain English
What this patent covers
This system improves search results by calculating a final score for images based on two distinct factors. First, it measures relevance by comparing search keywords to metadata associated with the image. Second, it calculates a quality score based on user ratings from various image forums, which is determined before any search query occurs. The system normalizes these ratings across different forums to ensure a five-star rating on one site is comparable to a ten-point scale on another. Finally, it combines these two scores to re-rank the search results, ensuring high-quality images appear higher than low-quality ones even if their relevance to the search term is identical.
The clever bit
The system treats the 'quality' of an image as a static, pre-calculated property that is independent of the search query, allowing the engine to mathematically merge objective quality with subjective relevance.
What it does not cover
- Does not cover ranking systems that rely solely on keyword matching without incorporating external user ratings.
- Does not cover real-time ranking adjustments based on user clicks or behavioral data collected during the search session.
- Does not cover ranking methods that fail to normalize ratings across different platforms.
- Does not cover systems that lack a pre-calculated quality score independent of the specific search query.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
PatentBrief Score
Impact Score
Strong
Citation count
33/40
Moderately cited
Claim breadth
6/20
Moderate scope
Recency
5/20
Granted 10–20 years ago
Assignee scale
20/20
Major company or institution
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$27K – $86K
Midpoint $54K · expired or expiring · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
The original legal language
Original claims
9 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Ma, W., Jing, F., & Zhang, L. (2010). How Search Engines Rank Images Using User Ratings (U.S. Patent No. 7,836,050). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/7836050/bing-search-ranking
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Search Engines Rank Images Using User Ratings cover?
A system that improves image search results by combining how well an image matches a search term with how highly users have rated that image elsewhere.
Who owns patent US 7836050?
Microsoft Corp owns this patent, granted in 2010.
When does this patent expire?
This patent is expected to expire on November 16, 2030, when the invention enters the public domain.
What is patent US 7836050 cited by?
This patent has been cited by 46 later patents that build on its ideas.
What problem does this patent solve?
This patent addresses the fundamental problem of search engine 'spam' and low-quality results. By shifting the focus from simple text matching to incorporating community-driven quality metrics, it helped search engines provide more useful results. It reflects the transition of the web from a static collection of pages to a social, community-rated ecosystem.
What does this patent NOT cover?
Does not cover ranking systems that rely solely on keyword matching without incorporating external user ratings.
Same assignee
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