# 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. - **Patent:** US 7836050 - **Original title:** Ranking content based on relevance and quality - **Owner:** Microsoft Corp - **Granted:** 2010 - **Status:** Public domain (expired) - **Times cited:** 46 - **Field:** software, ai_ml, ecommerce ## What it does 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. ## 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. ## 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. ## Real-world examples 1. Google Image Search results 2. Bing Image Search 3. Pinterest search ranking 4. Stock photo site search algorithms ## Why it matters 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. ## 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. **Full plain-English explainer:** https://patentbrief.org/patent/us/7836050/bing-search-ranking **Original patent:** https://patents.google.com/patent/US7836050 --- _Source: PatentBrief — https://patentbrief.org. Patent facts are from public records; the plain-English explanation is PatentBrief's._ ## Related patents Semantically similar inventions in the PatentBrief corpus: - [How Google Uses User Feedback to Rank Websites by Quality](https://patentbrief.org/patent/us/8615514/evaluating-website-properties-by-partitioning-user-feedback) — A method for Google to judge a website's quality by looking at how users interact with its search results across different categories of search queries. - [How Facebook Ranks Search Results Based on Your Friends' Activity](https://patentbrief.org/patent/us/8914392/facebook-events) — A method for ranking search results by prioritizing links that your social network friends have clicked on previously. - [How Computers Automatically Organize and Search Photos Using Contextual Data](https://patentbrief.org/patent/us/8862582/amazon-redshift) — A system for indexing images by attaching descriptive data to objects within them and adjusting search rankings based on how often a user searches for those specific items. - [How Websites Get Ranked by Importance](https://patentbrief.org/patent/us/6285999/google-pagerank) — This patent describes a computer method for scoring documents in a linked database, like the internet, by considering the importance of other documents that link to them, helping search engines find better results. - [How Google's Patent Scores Authors and Posts on Messaging Systems](https://patentbrief.org/patent/us/8606792/facebook-timeline) — Google's 2013 patent describes a system for ranking authors and their posts on a messaging platform based on user interactions and subscriptions, influencing content visibility.