Microsoft technology licensing, llc (20240338414). INTER-DOCUMENT ATTENTION MECHANISM simplified abstract
Contents
INTER-DOCUMENT ATTENTION MECHANISM
Organization Name
microsoft technology licensing, llc
Inventor(s)
Chenyan Xiong of Bellevue WA (US)
Chen Zhao of Greenbelt MD (US)
Corbin Louis Rosset of Seattle WA (US)
Paul Nathan Bennett of Redmond WA (US)
Saurabh Kumar Tiwary of Bellevue WA (US)
INTER-DOCUMENT ATTENTION MECHANISM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338414 titled 'INTER-DOCUMENT ATTENTION MECHANISM
The abstract of this patent application discusses natural language processing using a neural network framework. One method involves propagating attention from one document to another and producing contextualized semantic representations of words in the second document based on this propagation. These representations can be used for various natural language processing operations.
- Propagation of attention from one document to another
- Production of contextualized semantic representations of words in the second document
- Basis for natural language processing operations
Potential Applications: - Text summarization - Sentiment analysis - Machine translation - Question answering systems
Problems Solved: - Improving the accuracy of natural language processing tasks - Enhancing the understanding of context in text data
Benefits: - Increased efficiency in processing large volumes of text data - Improved accuracy in language understanding tasks
Commercial Applications: - Text analytics software for businesses - Chatbot development platforms - Content recommendation systems for online platforms
Questions about Natural Language Processing: 1. How does the propagation of attention improve the performance of natural language processing tasks? 2. What are the key differences between contextualized semantic representations and traditional word embeddings?
Frequently Updated Research: - Stay updated on advancements in neural network-based natural language processing techniques for improved performance.
Original Abstract Submitted
this document relates to natural language processing using a framework such as a neural network. one example method involves obtaining a first document and a second document and propagating attention from the first document to the second document. the example method also involves producing contextualized semantic representations of individual words in the second document based at least on the propagating. the contextualized semantic representations can provide a basis for performing one or more natural language processing operations.
