Quote Extraction and Ranking for Mobile Content
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Solution Overview
Problem
Current technologies lack efficient methods for analyzing and ranking quotes and named entities within content items, particularly in mobile devices, which hinders the delivery of high-quality, task-oriented content to users.
Innovation Solution
A computer-implemented method that identifies quotes and named entities within content items, provides identification information, and ranks quotes based on various criteria such as position, occurrence, and information availability, to deliver the best quotes and content to users through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated quote extraction and ranking systems are implemented, then content quality and user engagement improve, but system complexity increases
Solution Approach 1:
The system segments the content analysis process into distinct modules: quote identification, named entity recognition, information extraction, and ranking. Each module handles a specific aspect of content processing, making the overall system more manageable and maintainable while delivering high-quality results
Solution Approach 2:
The system introduces intermediary components such as the quote identification module and named entity recognition module that bridge the gap between raw content and final ranked quotes. These intermediaries process and structure information in manageable stages, reducing system complexity while improving reliability
2Loss of information
If comprehensive identification information is extracted and provided, then information completeness improves, but data processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-identifying and structuring named entities and their associated information during the initial analysis phase. This preparation work is done before the ranking process, allowing comprehensive information to be retrieved without adding processing time during the critical ranking stage
Solution Approach 2:
The system extracts comprehensive identification information including position, organization, title, and geographical location - more information than minimally required. This excessive action ensures information completeness while the modular architecture prevents proportional increases in processing time by efficiently managing each information type
3Measurement precision
If multiple quotes are ranked and analyzed, then content selection quality improves, but computational resources increase
Solution Approach 1:
The system changes parameters by using multiple ranking criteria (position in content, occurrence frequency, information completeness) to evaluate quotes. This multi-parameter approach improves ranking accuracy while the system efficiently manages computational resources by processing each parameter independently through specialized modules
Data Source
AI summary
Embodiments of the present disclosure may be utilized to analyze a content item comprising text to identity: a quote, a named entity that is the source of the quote (e.g., a person or organization such as a company), and identification information for the named entity (such as a title of the person giving the quote). Quotes may also be ranked to determine, for example, the best quotes to include in an article.