Techniques for Improved User Experience Prediction
Summary
The USPTO published patent application US20260099694A1 titled 'Techniques for Improved User Experience Prediction' filed on October 8, 2024. The application discloses a computer-implemented method that applies machine learning models to sequences of web pages and associated metrics data to generate user experience values using neural network embeddings and hidden layers.
What changed
The USPTO published a patent application disclosing machine learning techniques for predicting user experience based on web page visit sequences and associated metrics data. The method involves generating embeddings of web page identifiers and processing them through multiple hidden layers to determine cross-effects and metrics-based modifications before outputting user experience values.\n\nFor technology companies and software developers, this patent application represents potential prior art in the user experience analytics and web personalization space. Organizations developing similar ML-based web analytics or UX prediction systems should review the claims to assess potential infringement risks once the patent is granted.
Archived snapshot
Apr 18, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
TECHNIQUES FOR IMPROVED USER EXPERIENCE PREDICTION
Application US20260099694A1 Kind: A1 Apr 09, 2026
Inventors
Akshay K. Saxena, Kamlesh Kumar, Biren Rajdev, Ankit Kindra, Stephen J. Kelley
Abstract
Techniques for improved user experience prediction are disclosed herein. An example computer-implemented method includes receiving a sequence of web pages visited by a user and applying a machine learning model to (i) the sequence of web pages and (ii) a set of metrics data corresponding to the sequence of web pages. Applying the machine learning model includes generating embeddings of web page identifiers associated with the sequence of web pages, determining, by a first hidden layer, a first modified embedding based on respective cross-effects associated with one or more other embeddings, determining, by a second hidden layer, a second modified embedding based on the set of metrics data associated with a respective first modified embedding, and outputting a user experience value for each second modified embedding. The example computer-implemented method further includes generating one or more data objects indicating one or more of the user experience values.
CPC Classifications
G06N 3/0442 G06N 20/10
Filing Date
2024-10-08
Application No.
18909648
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