Personalized Content Summarization for Electronic Messages
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Solution Overview
Problem
Existing communication systems fail to effectively summarize external content referenced in electronic messages, requiring recipients to sift through lengthy documents or irrelevant information, which can be time-consuming and inefficient.
Innovation Solution
A system that generates personalized summaries of external content by analyzing user interests and preferences, using an indexing engine and ranking engine to extract key points and present them in a relevant format within the message, adapting to the recipient's interests and context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If external content is included in electronic messages, then information completeness is improved, but message length and processing time increase
Solution Approach 1:
The system extracts and summarizes key information from external content into a condensed format that can be included directly in the message body. This extraction process separates essential information from the full external content, allowing recipients to access key points without retrieving or reading the complete external documents, thereby reducing processing time while maintaining information completeness.
Solution Approach 2:
The system acts as an intermediary between external content and the message recipient by generating automated summaries. This intermediary process transforms external content into a message-appropriate format that preserves essential information while reducing the time burden on recipients, effectively mediating between information completeness and processing efficiency.
2Loss of information
If external content is referenced in messages, then communication richness is improved, but recipient effort to comprehend increases
Solution Approach 1:
The system extracts essential information from external content and presents it in a condensed summary format within the message. This extraction reduces the comprehension effort required by recipients while preserving communication richness, as key points are readily available without requiring recipients to access or navigate external documents.
Solution Approach 2:
The system applies local quality by providing summarized content specifically at the message level where it is most needed, rather than requiring uniform access to all external content. This localized summarization ensures that recipients receive exactly the information they need in the context of the message, reducing comprehension effort while maintaining communication richness.
3Adaptability or versatility
If personalized summaries are generated, then relevance to recipient interests is improved, but system complexity increases
Solution Approach 1:
The system implements a multi-functional architecture that combines interest profile management, content analysis, and summary generation within a unified framework. This universal system handles multiple tasks (profiling, analysis, summarization, personalization) through integrated components, reducing overall system complexity while maintaining adaptability to recipient interests.
Solution Approach 2:
The system performs preliminary actions by pre-processing external content and pre-establishing recipient interest profiles before message delivery. This preliminary preparation enables personalized summarization without adding complexity during the actual message processing, as the heavy lifting of content analysis and interest matching is completed in advance.
4Productivity
If automated summarization is implemented, then information delivery efficiency is improved, but processing resources increase
Solution Approach 1:
The system applies partial action by generating summaries that include only the essential information needed for effective communication, rather than processing or summarizing all external content in full detail. This selective summarization maintains information delivery efficiency while reducing processing resources, as the system focuses computational effort only on extracting and presenting key points rather than analyzing entire external documents.
Data Source
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AI summary
A system detects a message from a sender to a recipient, the message including a reference to external content. The system accesses a user model comprising interest information about interests of the sender or the recipient. The system identifies interest content from the external content as relevant to an interest from the interest information, generates a summarized content from the external content and based on the interest content and containing only a subset of information in the external content, and modifies the message to include the summarized content in the message.