Microsoft technology licensing, llc (20240346233). EFFICIENT GENERATION OF REVIEW SUMMARIES simplified abstract
Contents
EFFICIENT GENERATION OF REVIEW SUMMARIES
Organization Name
microsoft technology licensing, llc
Inventor(s)
Edy Daniel Paulino of Bellevue WA (US)
Kyle Matthew Unger of Seattle WA (US)
Judah Gabriel Himango of Monroe WA (US)
Wey Hsuan Low of Seattle WA (US)
EFFICIENT GENERATION OF REVIEW SUMMARIES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346233 titled 'EFFICIENT GENERATION OF REVIEW SUMMARIES
Simplified Explanation: This patent application describes methods, computer systems, computer storage media, and graphical user interfaces for efficiently generating review summaries. It involves obtaining reviews associated with an item, selecting a set of reviews based on attributes, inputting a model prompt into a machine learning model, and obtaining a review summary as output.
Key Features and Innovation:
- Obtaining reviews associated with an item
- Selecting reviews based on attributes
- Generating a model prompt for a machine learning model
- Obtaining a review summary as output
Potential Applications: This technology can be applied in e-commerce platforms, product review websites, and any other platform where summarizing reviews efficiently is essential.
Problems Solved: This technology addresses the challenge of efficiently summarizing a large number of reviews associated with a particular item.
Benefits:
- Saves time by providing concise summaries of reviews
- Helps users make informed decisions based on summarized information
- Enhances user experience by presenting information in a clear and organized manner
Commercial Applications: The technology can be used in e-commerce websites, review aggregators, and online marketplaces to improve the browsing and decision-making experience for users.
Prior Art: Readers can explore prior art related to machine learning models for text summarization and review aggregation to understand the existing landscape in this field.
Frequently Updated Research: Stay updated on advancements in machine learning models for text summarization and natural language processing to enhance the efficiency and accuracy of review summaries.
Questions about Review Summaries: 1. How can this technology impact the efficiency of online shopping experiences? 2. What are the potential limitations of using machine learning models for generating review summaries?
Original Abstract Submitted
methods, computer systems, computer-storage media, and graphical user interfaces are provided for efficiently generating review summaries. in embodiments, reviews associated with an item are obtained. a set of the reviews are then determined or selected based on an attribute associated with the corresponding review. thereafter, a model prompt to be input into a trained machine learning model is generated. the model prompt can include an indication of the item and the determined set of the reviews. as output from the trained machine learning model, a review summary that summarizes the set of the reviews associated with the item is obtained.
