Automatic Headline Generation via Syntactic Pattern Matching
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Solution Overview
Problem
Current methods for generating headlines for news articles are not scalable for web-crawled data due to manual intervention requirements and are often based on consistent content formatting, which varies in web articles, leading to issues with grammar errors and the need for human supervision.
Innovation Solution
A system learns sets of equivalent syntactic patterns from a corpus of documents to identify and generate headlines, processing input documents for matching patterns that reflect the main event, allowing for automatic headline generation without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual methods are used to generate headlines, then headline quality can be maintained, but scalability is poor due to high manual intervention requirements
Solution Approach 1:
The patent replaces manual headline generation with an automated system that uses syntactic pattern learning. The system learns from existing headlines and applies learned patterns to generate new headlines automatically, eliminating the need for manual intervention while maintaining quality.
Solution Approach 2:
The system performs self-learning by processing existing headlines to extract and store syntactic patterns. Once trained, the system can autonomously generate headlines for new articles without requiring human supervision or intervention, achieving self-service operation.
2Ease of manufacture
If existing solutions use main passage as headlines, then headline generation is simple, but grammar errors occur due to word reordering techniques
Solution Approach 1:
The system copies and adapts proven syntactic patterns from existing headlines rather than creating new structures. By selecting from pre-learned valid patterns and filling in entity-specific information, the system ensures grammatical correctness while maintaining simplicity in the generation process.
3Measurement precision
If manual supervision is used for headline selection, then headline accuracy is maintained, but scalability is limited to single documents
Solution Approach 1:
The system segments the headline generation task into two phases: a learning phase where syntactic patterns are extracted from multiple documents, and an application phase where patterns are matched to new documents. This segmentation enables the system to handle multiple documents independently while maintaining accuracy through pattern-based selection.
Data Source
AI summary
Sets of equivalent syntactic patterns are learned from a corpus of documents. A set of one or more input documents is received. The set of one or more input documents is processed for one or more expressions that match a set of equivalent syntactic patterns from among the sets of equivalent syntactic patterns. A syntactic pattern from among the set of equivalent syntactic patterns is selected for a headline. The syntactic pattern reflects a main event described by the set of one or more input documents. The headline is generated using the syntactic pattern.