US 5,918,014 · Granted 1999-06-29

The Patent That Invented Your Personalized Ad Feed

Before Netflix recommendations or Spotify playlists, this 1999 patent figured out how to show you ads based on what people similar to you clicked on. It tracks your browsing habits, finds your "community" of people with matching tastes, and serves ads that worked for them — basically the ancestor of today's targeted advertising.

Curated and verified by the IsItPatented Editorial team

The plain-English version

What it protects

The claim covers a system for identifying groups of web users with similar browsing and clicking patterns, then using those similarities to predict which ads will appeal to a specific person. What's protected here is the method of tracking individual user activities (like clicks and page visits), calculating similarity scores between users, clustering them into communities, and then selecting advertisements to display based on what the community tends to engage with.

Why it matters

This patent is a foundational piece of modern digital advertising. It describes the core logic behind collaborative filtering applied to ads — the idea that your behavior predicts your preferences, and your peers' behavior predicts yours. Filed in 1996 and granted in 1999, it arrived at the moment the web was exploding, before Google existed. It locked down the principle that would eventually power Facebook ads, Amazon recommendations, and the entire personalization economy.

Real-world use

Every time you see a targeted ad on a website that seems oddly perfect for you, it's likely using logic this patent protects — matching your profile to thousands of similar users and showing you what their crowd clicked on.

Original USPTO abstract

On the World Wide Web, and other interactive media, it is possible to show different ads to different people who are simultaneously viewing the same content. This invention is based on the fact that people who have shown a tendency for similar likes and dislikes in the past will show a tendency for such similarities in the future. Those people who strongly display such similarities with respect to a particular person ("the subject") are referred to as that person's "community." If the members of a subject's community tend to click on a particular Web ad, then it is likely that the subject will also tend to click on that ad. This invention combines techniques for: determining the subject's community, and determining which ads to show based on characteristics of the subject's community. The information used to determine whether a given individual should be in the subject's community is gleaned from the individual's activities in the interactive medium. Means are provided to track a consumer's activities so all the information he generates can be tied together in the database, e.g. by means of "cookies;" or by software running on the consumer's computer, such as an in-line plug-in, a screensaver working in conjunction with the Web browser, or the Web browser itself. A measure of similarity between individuals is generated. The individuals with the greatest calculated similarity become the subject's community; e.g. clusters are formed of groups of very similar consumers. Ads are presented to the subject based on his community, optionally selected based on demographics associated with the community.

Patent details

Publication number: US 5,918,014
Filing date: 1996-12-26
Grant date: 1999-06-29
Assignee: Athenium, L.L.C.
Inventor(s): ROBINSON; GARY B.
CPC class: H04L12/1859

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