US 5,754,939 · Granted 1998-05-19

The 1998 Patent That Invented Your News Feed Algorithm

Imagine a system that learns what news articles YOU care about by analyzing which words appear most in articles you like, then automatically ranks all available articles to show you the best matches first. This patent describes exactly that: a personalization engine that matches readers to content and protects user privacy by hiding their preferences from companies tracking them.

Curated and verified by the IsItPatented Editorial team

The plain-English version

What it protects

The claim covers a system that automatically creates a profile of each user's interests by analyzing the articles or content they engage with, then compares those profiles against profiles of available content (built on word frequency and relevance analysis) to rank and recommend items most likely to appeal to that specific user. What's protected here is the combination of: building individual user interest summaries, scoring content objects against those summaries, and using a privacy-protecting proxy server so third parties cannot see or track a user's profile without permission.

Why it matters

Filed in 1995 and granted in 1998, this patent describes the foundational mechanics of modern recommendation systems and personalized content feeds—technology now central to Google News, Reddit, Facebook, TikTok, and every streaming service. By locking down the method of profiling users and matching them to content algorithmically, it established early intellectual property around a category that would become one of the most valuable and contested in the internet era, though the patent itself has since expired.

Real-world use

Every time Netflix suggests a movie you might like, or YouTube's homepage shows you videos tailored to your watch history, a descendant of this matching logic is at work—analyzing patterns in your behavior and ranking options just for you.

Original USPTO abstract

This invention relates to customized electronic identification of desirable objects, such as news articles, in an electronic media environment, and in particular to a system that automatically constructs both a "target profile" for each target object in the electronic media based, for example, on the frequency with which each word appears in an article relative to its overall frequency of use in all articles, as well as a "target profile interest summary" for each user, which target profile interest summary describes the user's interest level in various types of target objects. The system then evaluates the target profiles against the users' target profile interest summaries to generate a user-customized rank ordered listing of target objects most likely to be of interest to each user so that the user can select from among these potentially relevant target objects, which were automatically selected by this system from the plethora of target objects that are profiled on the electronic media. Users' target profile interest summaries can be used to efficiently organize the distribution of information in a large scale system consisting of many users interconnected by means of a communication network. Additionally, a cryptographically-based pseudonym proxy server is provided to ensure the privacy of a user's target profile interest summary, by giving the user control over the ability of third parties to access this summary and to identify or contact the user.

Patent details

Publication number: US 5,754,939
Filing date: 1995-10-31
Grant date: 1998-05-19
Assignee: Herz; Frederick S. M. / Eisner; Jason M. / Ungar; Lyle H. / Marcus; Mitchell P.
Inventor(s): HERZ; FREDERICK S. M., EISNER; JASON M., UNGAR; LYLE H., MARCUS; MITCHELL P.
CPC class: H04N21/44222

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