Source Link Determination for News Aggregators
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Solution Overview
Problem
News aggregator systems face challenges in accurately identifying the original source of content when multiple published objects share the same theme but have differing content, leading to user dissatisfaction and increased energy and bandwidth consumption due to repeated searches for consistent information.
Innovation Solution
A method and system that determine a source link by analyzing the themes of published objects, extracting potential source links, generating link-cluster pairs, and using machine learning to identify the source link associated with the original theme, which is then associated with each published object in the theme cluster, allowing for the retrieval and transmission of the source link upon request.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If news aggregator systems present multiple published objects with the same theme but different content, then users are exposed to diverse content variations, but users experience dissatisfaction and perform repeated searches due to inability to locate the original source
Solution Approach 1:
The system performs preliminary analysis of published objects to identify theme clusters and extract potential source links before user requests. By pre-processing content and organizing it into thematic clusters with associated source information, the system prepares the data structure in advance to enable rapid source identification when users query, thereby reducing their search time without compromising content diversity
Solution Approach 2:
The system introduces an intermediary mechanism (source link extraction and association module) that connects published objects to their original sources. This intermediary layer analyzes the content, identifies potential source links, and associates them with theme clusters, allowing users to efficiently navigate from diverse content variations back to the original source without performing repeated manual searches
2Reliability
If users perform repeated searches to locate consistent information across different published objects, then they can find the original source, but energy and bandwidth consumption increase
Solution Approach 1:
The system performs preliminary extraction and verification of source links from published objects, organizing them into theme clusters before user requests. By pre-identifying and storing the relationship between published objects and their sources, the system eliminates the need for users to perform repeated searches, thereby reducing energy consumption while maintaining information consistency through accurate source attribution
Solution Approach 2:
The system implements a feedback mechanism where source link extraction results are stored and reused for subsequent queries. By analyzing published objects, extracting source links, and feeding this information back into the system for future reference, the system avoids redundant analysis and reduces energy consumption while ensuring consistent identification of original sources
3Measurement precision
If the system analyzes themes and extracts potential source links for each published object, then source identification accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the source identification process into distinct modular components: theme analysis module, potential source link extraction module, link-cluster pair generation module, and source link determination module. Each module performs a specific function and can be independently optimized or replaced, improving source identification accuracy through specialized processing while managing system complexity through modular architecture
Solution Approach 2:
The system introduces intermediary data structures (theme clusters, link-cluster pairs, and feature sets) that bridge the gap between raw published objects and final source identification. These intermediaries organize and structure the data flow, enabling accurate source determination through systematic analysis while maintaining manageable system complexity through clear data transformation stages
4Ease of operation
If the system stores and associates source links with each published object in theme clusters, then user satisfaction improves through easy source access, but data storage requirements increase
Solution Approach 1:
The system extracts only the essential source link information from published objects and stores it in an optimized format associated with theme clusters. By taking out only the critical source identification data rather than storing complete object replicas or redundant information, the system enables easy source access for users while minimizing the quantity of stored data through selective extraction and efficient association
Data Source
AI summary
There is disclosed a method of determining a source link, the source link being associated with a source object, the method executable on a server, the method comprising: acquiring a plurality of published objects; creating a plurality of theme clusters by clustering the plurality of published objects by its respective theme; extracting from each published object contained in a respective theme cluster, at least one potential source link; generating, at least one link-cluster pair, where, for each link-cluster pair, a set of features representative of a property of the link-cluster pair is generated; based on the set of features associated with each link-cluster pair, determining the source link associated with the source object for the given theme cluster; and associating the source link with each of the plurality of published objects clustered in the associated theme cluster.