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Yes, the story from The Washington Examiner was shared on
Posted on: June 18, 2025 at 15:57:37 CT
KCT-BoneTiger MU
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MSN for you and your algorithm
How MSN ranks content
MSN publishes news stories, photo galleries, and videos from thousands of publishers globally and promotes this content across Microsoft products, including Microsoft Edge, Microsoft Windows, MSN.com, and the MSN mobile app.
Each time a consumer views the MSN feed, it refreshes with the latest personalized content. Based on various signals, algorithms select and order content in the feed with editorial oversight. This ranking content system is designed to engage and inform, choosing stories that are the most relevant to each person, while also ensuring the content is timely, newsworthy, high-quality, and safe for work and home.
The relative importance of these parameters may vary each time a news feed is viewed by a user. The algorithms are always evolving as we continually identify and improve signals and experiment with new features.
User relevance
Microsoft delivers every consumer a personalized news feed to meet each person’s unique set of interests and preferences for content. At the core of this personalization are algorithms that match user preferences with document understanding. These algorithms are designed to select the most relevant content for each user.
A user’s preferences are learned over time by the system through two approaches:
Explicit personalization. The algorithm respects how users manually configure their settings, including actions like following certain topics, liking or disliking specific content, or indicating a publisher preference.
Implicit personalization. In compliance with a user’s privacy settings, as a person reads content and engages with Microsoft’s products, the stories are analyzed for patterns to better understand the user’s preferences. The algorithms look both for long-term and short-term patterns for each user, acknowledging that content interests may vary in the short term, while exhibiting different long-term tendencies. (Read more about Microsoft Privacy here)
Machine-learning algorithms drive deep document understanding beyond simply recognizing ‘topics’: The system performs analysis on each document to get insights based on text and metadata and converts the content into a mathematical model.
http://helpcenter.msn.com/kb/articles/77-content-ranking
How MSN ranks content
MSN publishes news stories, photo galleries, and videos from thousands of publishers globally and promotes this content across Microsoft products, including Microsoft Edge, Microsoft Windows, MSN.com, and the MSN mobile app.
Each time a consumer views the MSN feed, it refreshes with the latest personalized content. Based on various signals, algorithms select and order content in the feed with editorial oversight. This ranking content system is designed to engage and inform, choosing stories that are the most relevant to each person, while also ensuring the content is timely, newsworthy, high-quality, and safe for work and home.
The relative importance of these parameters may vary each time a news feed is viewed by a user. The algorithms are always evolving as we continually identify and improve signals and experiment with new features.
User relevance
Microsoft delivers every consumer a personalized news feed to meet each person’s unique set of interests and preferences for content. At the core of this personalization are algorithms that match user preferences with document understanding. These algorithms are designed to select the most relevant content for each user.
A user’s preferences are learned over time by the system through two approaches:
Explicit personalization. The algorithm respects how users manually configure their settings, including actions like following certain topics, liking or disliking specific content, or indicating a publisher preference.
Implicit personalization. In compliance with a user’s privacy settings, as a person reads content and engages with Microsoft’s products, the stories are analyzed for patterns to better understand the user’s preferences. The algorithms look both for long-term and short-term patterns for each user, acknowledging that content interests may vary in the short term, while exhibiting different long-term tendencies. (Read more about Microsoft Privacy here)
Machine-learning algorithms drive deep document understanding beyond simply recognizing ‘topics’: The system performs analysis on each document to get insights based on text and metadata and converts the content into a mathematical model.
http://helpcenter.msn.com/kb/articles/77-content-ranking
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Yes, the story from The Washington Examiner was shared on - KCT-BoneTiger MU - 6/18 15:57:37