Automated Content Summary Generation via Text Mining
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Solution Overview
Problem
Existing web content management systems lack the ability to automatically generate summaries for content items, leading to instances where no relevant summary is available or the summary does not meet user needs in terms of length or device compatibility.
Innovation Solution
A system that includes a processor, data repository, and a text mining engine, allowing users to select content items and specify summary parameters such as size or device type, enabling the automatic generation of summaries as independent content items that can be edited and stored separately, with metadata and keywords.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing web content management systems retrieve existing summaries associated with images, then summaries can be provided for content items, but there are instances where no relevant summary is available or the summary does not meet user needs in terms of length or device compatibility
Solution Approach 1:
The system enables users to specify their own summary parameters (length, device type, format) and the text mining engine automatically generates summaries according to these user-defined requirements, making the system self-serve user needs without manual intervention
Solution Approach 2:
The system allows dynamic adjustment of summary parameters such as length, format, and device compatibility, enabling the same content item to generate different summaries tailored to different user needs and contexts
2Productivity
If summaries are generated manually by users, then summary quality can be controlled, but manual effort and time consumption increase
Solution Approach 1:
The system replaces the manual mechanical process of writing summaries with an automated text mining engine that uses algorithms to extract and generate summaries, eliminating manual effort while maintaining efficiency
Solution Approach 2:
The text mining engine automatically performs summary generation based on input content and parameters, serving the system's own function of creating summaries without requiring human intervention
3Adaptability or versatility
If summaries are stored as metadata associated with content items, then summaries are readily available, but summaries cannot be independently edited, reused, or managed as separate content items
Solution Approach 1:
The system separates summaries from the original content items, treating them as independent content items with their own identifiers, metadata, and management capabilities, allowing summaries to be independently edited and reused
Solution Approach 2:
The system adds a new dimension to content management by creating a hierarchical structure where summaries exist as separate, reusable content items that can be independently managed, edited, and reused across different contexts
Data Source
AI summary
Systems for generating content summaries in a web content management service, wherein in one embodiment a digital page editor and a component browser are launched to enable selection of a first content item. A summary of the first content item is automatically generated according to parameters that may have default values or values set by a user. The parameters may specify a size for the summary as a percentage of the first content item's size, as a particular number of lines, characters or words, as a size for a particular type of device, etc. The automatically generated summary is provided to the digital page editor, which can edit it and add it to the digital page. The summary is stored in a content repository as an independent summary content item with its own metadata.