18661397. INTER-DOCUMENT ATTENTION MECHANISM simplified abstract (Microsoft Technology Licensing, LLC)
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 18661397 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.
- Simplified Explanation:
This patent application focuses on using a neural network framework for natural language processing. It describes a method where attention is transferred from one document to another to create contextualized semantic representations of words for processing.
- Key Features and Innovation:
- Utilizes a neural network framework for natural language processing - Propagates attention between documents to create contextualized semantic representations - Enables various natural language processing operations based on these representations
- Potential Applications:
- Text summarization - Sentiment analysis - Machine translation - Question answering systems
- Problems Solved:
- Enhances the understanding of individual words in a document - Improves the accuracy of natural language processing tasks - Facilitates more efficient language processing operations
- Benefits:
- Increased accuracy in language processing tasks - Enhanced contextual understanding of words - Improved performance of natural language processing systems
- Commercial Applications:
"Enhancing Natural Language Processing Efficiency with Neural Networks"
This technology can be applied in various industries such as: - Customer service chatbots - Content recommendation systems - Voice assistants - Sentiment analysis tools
- Questions about Natural Language Processing:
1. How does the propagation of attention between documents improve natural language processing tasks? 2. What are the potential limitations of using a neural network framework for language processing?
- Frequently Updated Research:
Stay updated on the latest advancements in neural network-based natural language processing to leverage cutting-edge technologies for improved language understanding and processing.
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.
