Event Evolutionary Graphs for Efficient News Processing
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Solution Overview
Problem
The exponential increase in news due to network and multimedia technology overwhelms users, requiring efficient sorting, refinement, and intuitive presentation of news information, while traditional methods fail to automatically associate related events and predict their impact.
Innovation Solution
Presenting and processing event evolutionary graphs that link events through nodes and directed edges, determined from media content, allowing extension with reference graphs to show related events and predict impacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If news information is presented in traditional formats, then information completeness is maintained, but information processing efficiency deteriorates due to the massive amount of news occupying valuable reading time
Solution Approach 1:
The patent segments news information into discrete event nodes within an evolutionary graph structure. Each event is extracted as an independent node with specific attributes (time, location, participants, actions), allowing the system to divide the massive news corpus into manageable, meaningful units that can be processed and presented efficiently without overwhelming users with raw text volume
Solution Approach 2:
The patent transforms traditional linear news presentation into a multi-dimensional event evolutionary graph structure. Events are organized across multiple dimensions including time evolution, causal relationships, and semantic connections, enabling users to navigate information through different dimensional perspectives rather than chronological order alone, thus reducing the time needed to comprehend complex news landscapes
2Measurement precision
If users manually search and filter event-related information, then information accuracy is improved, but operation complexity increases making the process very cumbersome
Solution Approach 1:
The patent implements self-service through automated event extraction and graph construction algorithms that automatically parse news content, identify event nodes, establish relationships between events, and build the evolutionary graph structure without user intervention. The system autonomously performs the filtering and organization tasks that would otherwise require manual user effort, while maintaining high information accuracy through structured data extraction
Solution Approach 2:
The event evolutionary graph serves as an intermediary structure between raw news data and user comprehension. Rather than requiring users to directly search and filter unstructured news text, the system introduces the graph structure as a mediator that pre-organizes information into navigable event nodes and relationships, dramatically simplifying the user's information seeking process while preserving accuracy through the structured representation
3Productivity
If isolated event information is presented, then information clarity is improved, but insight depth deteriorates as users cannot understand the ins and outs of events or predict their impact
Solution Approach 1:
The patent merges multiple isolated event nodes into a unified event evolutionary graph that preserves both individual event clarity and contextual relationships. Events are combined through defined relationship types (causal, temporal, spatial, semantic connections), allowing users to understand each event in isolation while simultaneously grasping its context within the broader event ecosystem, thus preventing information loss without sacrificing clarity
4Quantity of substance
If comprehensive news coverage is provided, then information completeness is improved, but device complexity increases requiring automated sorting and refinement systems
Solution Approach 1:
The patent implements a universal event extraction framework that handles diverse news types and formats through a single standardized graph structure. The system uses multi-functional processing algorithms that can extract events from different news genres, languages, and formats using the same core methodology, reducing system complexity by avoiding the need for separate processing pipelines for each news type while maintaining comprehensive coverage
Data Source
AI summary
According to embodiments of the present disclosure, a method and apparatus for information presenting are provided. The method includes presenting a first event evolutionary graph corresponding to a media content. The first event evolutionary graph includes at least a first node representing a first event, a second node representing a second event, and a first directed edge representing a first event relationship between the first event and the second event. The first event, the second event, and the first event relationship are determined from the media content. The method further includes presenting a second event evolutionary graph in association with the first event evolutionary graph. The second event evolutionary graph comprises at least a third node representing a third event. A first event factor of at least one event of the first event or the second event matches a second event factor of the third event.