Web Content Context Retrieval with Zoom-Out Summaries
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Solution Overview
Problem
Users face the challenge of needing to perform additional searches to obtain contextual information for online articles, which is time-consuming and inefficient.
Innovation Solution
A system and method that automatically generates a zoom-out summary of contextual information for online articles by extracting relevant information from the article, retrieving associated data from a database using a knowledge graph, and presenting it as a zoom-out summary to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users perform additional searches to obtain contextual information, then they can access background information, but it is time-consuming and inefficient
Solution Approach 1:
The system performs preliminary action by automatically extracting relevant information from the current article and retrieving associated contextual information from a database before the user needs it. The zoom-out summary is pre-generated and ready for immediate display when the user activates the zoom-out option, eliminating the need for users to perform manual searches.
Solution Approach 2:
The system provides self-service by automatically generating the zoom-out summary based on the current article content without requiring user intervention for information extraction. The system serves itself by using the article's own content as input to generate relevant contextual summaries, reducing the burden on users.
2Loss of information
If users manually determine keywords for additional searches, then they can find specific information, but it requires effort and is time-consuming
Solution Approach 1:
The system performs self-service by automatically extracting relevant information and determining search keywords from the current article content. The story information extractor automatically identifies key concepts and retrieves associated contextual information without requiring users to manually determine search keywords, significantly reducing operational effort.
Solution Approach 2:
The system introduces an intermediary - the automated information extraction and retrieval mechanism - that mediates between the user's reading needs and the contextual information in the database. This intermediary automatically bridges the gap by extracting relevant information and presenting it through the zoom-out summary, eliminating the need for users to manually search.
3Productivity
If the system automatically generates zoom-out summary, then user efficiency is enhanced, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the contextual information retrieval process into distinct functional modules: story information extraction, relevant past content retrieval, and zoom-out summary generation. Each module handles a specific task independently, making the overall complex system more manageable and maintainable while achieving automated efficient operation.
Data Source
AI summary
The present teaching relates to providing contextual information to web content. Relevant information is extracted from a current article that a user is reviewing. Contextual information associated with the current article is retrieved from a database based on the extracted relevant information. A zoom-out summary of the contextual information is automatically generated to characterize the background of the current article. A zoom-out option is presented to the user that allows the user to review, once the option is activated, the zoom-out summary to understand the background of the current article.