# How Streaming Services Automatically Build Custom Radio Stations > A method for streaming services to create custom music radio stations by analyzing genre percentages and artist relationships to pick the best songs. - **Patent:** US 10108619 - **Original title:** Station library creaton for a media service - **Owner:** Gracenote Inc - **Granted:** 2018 - **Status:** Active - **Times cited:** 3 - **Field:** consumer_electronics, software, ai_ml ## What it does This patent describes a system that builds a custom music station based on a 'seed,' such as a specific song or artist. It creates a 'station descriptor profile' that acts as a blueprint, breaking down the desired music into specific genre percentages. The system then compares candidate songs against this blueprint using a similarity score, while also applying 'boost values' for factors like language, artist relationships, or release dates. Finally, it selects the songs with the highest combined relevancy scores to populate the station library. ## What it does NOT cover - Does not cover manual playlist creation where a human selects every song. - Does not cover simple random shuffling of a user's entire library. - Does not cover hardware-based audio processing or signal compression techniques. - Does not cover social media-based music sharing or peer-to-peer recommendation systems. ## The clever bit The system uses 'focus genre profiles' that assign specific percentage weights to genres, allowing the algorithm to maintain a precise stylistic balance in a station rather than just picking songs that sound vaguely similar. ## Real-world examples 1. Spotify Radio 2. Pandora stations 3. Apple Music station generation 4. YouTube Music radio features ## Why it matters This technology is fundamental to the 'radio' features found in modern music streaming services. By automating the creation of genre-balanced stations, services like Spotify or Pandora can keep users engaged without requiring them to curate their own music, which is essential for the subscription-based streaming business model. ## Frequently asked questions ### What does How Streaming Services Automatically Build Custom Radio Stations cover? A method for streaming services to create custom music radio stations by analyzing genre percentages and artist relationships to pick the best songs. ### Who owns patent US 10108619? Gracenote Inc owns this patent, granted in 2018. ### When does this patent expire? This patent is expected to expire on October 23, 2038, when the invention enters the public domain. ### What is patent US 10108619 cited by? This patent has been cited by 3 later patents that build on its ideas. ### What problem does this patent solve? This technology is fundamental to the 'radio' features found in modern music streaming services. By automating the creation of genre-balanced stations, services like Spotify or Pandora can keep users engaged without requiring them to curate their own music, which is essential for the subscription-based streaming business model. ### What does this patent NOT cover? Does not cover manual playlist creation where a human selects every song. **Full plain-English explainer:** https://patentbrief.org/patent/us/10108619/microsoft-edge-browser **Original patent:** https://patents.google.com/patent/US10108619 --- _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 Music Apps Learn What You Don't Want in Playlists](https://patentbrief.org/patent/us/12277178/media-content-item-recommendation-system) — This patent describes how a music streaming service learns what kinds of songs or artists a user dislikes for their playlists by tracking what they repeatedly ignore, then uses that information to avoid recommending similar things in the future. - [How Computers Automatically Tag Movies and Shows Better](https://patentbrief.org/patent/us/12135756/content-recommendation-system-with-weighted-metadata-annotations) — This patent describes a system for automatically improving how movies, TV shows, and other media are tagged with descriptive labels by comparing them to similar content using a special ratio. - [How a Recommendation System Learns What You Really Want to Watch](https://patentbrief.org/patent/us/12118030/dynamic-feedback-in-a-recommendation-system) — This patent describes a media recommendation system that creates a unique user profile, uses it to pick a starting point, and then dynamically adjusts a list of suggestions based on what you've already watched and your real-time feedback. - [How to Play Any Media Playlist by Converting it to a Standard Format](https://patentbrief.org/patent/us/6990497/dynamic-streaming-media-management) — This patent describes a system that takes media playlists in various formats, converts them into a single standard format, and then streams the referenced content, even allowing for dynamic changes during playback. - [How a Recommendation System Uses Dislikes to Suggest New Content](https://patentbrief.org/patent/us/11416536/content-recommendation-system-11416536) — Comcast's patent describes a content recommendation system that finds users with similar tastes by focusing on what content they both dislike, especially popular disliked items, to suggest new shows or movies.