Invented by Gisolfi; Daniel A., Scamahorn; Douglas Brian, Clavey; Bruce, Noble; Lise W.
In today’s world, digital content is everywhere. Making sure that online information is trustworthy, easy to find, and managed well has never been more important. A recent patent application presents a new way to use software to measure how much you can trust a piece of digital content, then manage that content based on a trust score. In this article, we break down what this invention means, why it matters, and how it works in simple terms.
Background and Market Context
Digital content runs modern organizations. Companies, schools, and even governments use content management systems (CMS) to create, share, and store articles, videos, rules, and more. A CMS acts like a digital library, helping groups work together to build and keep track of content. As organizations grow, so does the amount of content they have to manage. This makes it hard to keep every piece of information up-to-date, accurate, and useful.
Traditionally, people called content managers or editors check and control what goes into the CMS. They follow rules and policies to keep the quality high. Still, several problems make their job tough:
First, the number of items in a CMS can grow into the thousands or more. One person or even a team can’t check everything. Second, content gets old or less accurate as time goes by, but it’s hard to know exactly when something is no longer reliable. Third, as more people create and edit content, keeping everything consistent is a big challenge. Last, finding the most reliable or current piece of information can be like searching for a needle in a haystack.
Authors who write content also face issues. If they’re new or not well-known, their work can be ignored, even if it’s good. Meanwhile, readers—people looking for answers—may have trouble figuring out which content is trustworthy and which is not. They might give feedback, but it often gets lost or is too little to make a difference.
To fix these problems, the market is looking for tools that can score the trustworthiness of content, help manage it automatically, and make it easier for readers to find the best information. This is where the patent application comes in, promising a smarter way to score and manage digital content using software.
Scientific Rationale and Prior Art
The main idea behind this invention is to bring objectivity and automation to content management. Before this, most CMS solutions depended on people to judge quality and trust. Some tools offered basic features, like version tracking or feedback forms, but they didn’t provide a systematic, automated way to measure how much you can trust a piece of content.
So, what have others tried before? Some systems use manual checklists or approval steps, where managers sign off on content. Others let users rate articles with stars or thumbs up. More advanced CMS platforms might use workflow rules, such as requiring a review before publishing. A few have tried machine learning to help with categorizing or tagging content, but not specifically for trustworthiness scoring.
There has also been some research into using artificial intelligence (AI) to spot fake news or low-quality posts, mostly on social media. These AI tools look at language patterns or check facts, but they’re often standalone—they don’t tie directly into the CMS process, and they rarely update scores over time as new feedback comes in or as content ages.
Another idea found in prior solutions is the “lifecycle” approach, where content moves through stages: draft, review, publish, archive. However, the decision to advance content often depends on a person making a judgment call. If trustworthiness changes—say, the information becomes outdated—there’s no easy way to re-check and update the content’s status automatically.
This patent builds on these ideas but moves beyond them. It introduces the use of scoring models that can be customized for different types of content, different lifecycle stages, and even different organizations. It leverages a mix of inputs—like user feedback, content age, author reputation, and API-based checks (such as AI analysis)—to calculate a trust score. It then uses this score to decide what should happen next with the content, such as promoting it, archiving it, or asking for more review. Importantly, the score can be updated as new data comes in, making the system dynamic and self-correcting.
Invention Description and Key Innovations
The core of this invention is a software platform that uses a scoring model to judge how trustworthy a piece of content is. Let’s break down how it works in simple steps:
First, the system provides a user interface (UI), which is a screen or dashboard that lets users (like content managers) create scoring models. These models are like recipes: you choose what ingredients (input variables) matter and how much weight to give each one. For example, you might say that user feedback counts for 30%, content age is 20%, and author reputation is 50%.
The inputs—what the system looks at to judge trustworthiness—can come from many places:
– The content itself (like how old it is or how many sources it cites).
– User feedback (like ratings, comments, or survey responses).
– Information about the author (such as how many trusted articles they’ve written before).
– Data from other content in the CMS (for example, how many other pieces link to this one).
– Results from an API, such as an AI checker that looks for signs of fake or AI-generated content.
Once a scoring model is created, the system can use it to automatically check any piece of content in the CMS. It gathers the needed data, plugs it into the model, and gets a trustworthiness score. This score is usually a number (say, from 1 to 100) or a label (like “high,” “medium,” or “low” trust).
What happens next depends on the score. The system can be set up with rules—if the content scores high, it might move forward to publication or get featured. If it scores low, it could be flagged for review, held back, or even archived. These decisions can be automated, so content managers don’t have to check every item by hand.
But the real power of this invention is that the trust score isn’t set in stone. As time goes on, the system collects new data—maybe users give more feedback, the author writes more articles, or the content gets older. The system can re-check the trust score automatically and change the content’s status if needed. For example, an article might be published at first, but if lots of users later say it’s outdated or wrong, its score drops and the system can move it to the archive or flag it for correction.
The scoring model is flexible. You can create different models for different types of content (like technical articles vs. blog posts) or different stages (like draft vs. published). The UI makes it easy to pick variables and set their weights, so organizations can customize how they judge trustworthiness.
The system also provides APIs so other software—like search engines—can access the trust scores. That way, the most trustworthy content can be shown at the top of search results, helping users find the best information faster.
Another innovation is the way the system uses trust scores to build “eminence” scores for authors. If an author consistently writes high-trust content, their reputation goes up, making their future work more visible and trusted by readers. This encourages authors to create better content and rewards those who do.
Finally, the software supports rules for managing notifications. For example, when a content’s trust score changes, the system can send alerts to the author or manager, letting them know what happened and what action was taken. This keeps everyone in the loop and makes it easier to keep the CMS organized.
Actionable Takeaways
If you’re responsible for managing digital content, this invention gives you a powerful new tool. You can:
– Set up scoring models that match your organization’s needs.
– Let the system monitor and manage content automatically, so you spend less time on manual reviews.
– Use trust scores to guide users to the best information and build author reputations fairly.
– Stay on top of changes with automatic notifications and easy-to-understand dashboards.
Most of all, you can build trust in your content library, making sure readers find accurate, up-to-date answers when they need them.
Conclusion
This patent application introduces a simple but powerful way to score and manage digital content using a mix of human feedback, author reputation, content data, and even AI-powered analysis. By turning trust into a number, the system makes content management easier, faster, and more reliable. It helps organizations keep their digital libraries accurate and useful, rewards good authors, and guides readers to the best information. As digital content keeps growing, inventions like this will be key to building trust online and making sure everyone can find the answers they need.
Click here https://ppubs.uspto.gov/pubwebapp/ and search 20250217487.