Media Guidance App Correlating Distributed Date Strings
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Solution Overview
Problem
Conventional systems fail to identify and correlate date information that is implicit or distributed across different parts of an electronic document, such as the title and body, using non-standard date formats, leading to incomplete calendar scheduling.
Innovation Solution
A media guidance application that identifies and correlates date information by parsing text strings within and outside document objects, using a hierarchical structure to combine partial date elements, even if they are not in standard formats, and determines their relative positions to generate a complete calendar schedule.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional systems use standard date format identification, then they can reliably identify explicit date information, but they fail to detect implicit or distributed date information across different document parts
Solution Approach 1:
The system segments date information detection into multiple independent modules: (1) identifying individual date-related text strings throughout the document, (2) determining their hierarchical relationships, and (3) correlating them to form complete date-time indicators. This segmentation allows the system to handle distributed date information by processing each part separately and then integrating them based on their positional and contextual relationships.
Solution Approach 2:
The system introduces a hierarchical dimension to organize date information, creating levels such as document-level dates, section-level dates, and element-level dates. By arranging date strings in a hierarchical structure based on their positions in the document, the system can correlate partial date elements from different levels to generate complete calendar schedule indicators, thus handling implicit and distributed date formats effectively.
2Loss of information
If the system correlates distributed date information from different document parts, then complete calendar schedules can be generated, but the system complexity increases due to hierarchical structure management
Solution Approach 1:
The system performs preliminary actions by first identifying and extracting all date-related text strings throughout the document before attempting to correlate them. It pre-processes the document by marking potential date elements and their positions, then uses these pre-identified elements to build the hierarchical structure. This preliminary identification reduces the complexity of subsequent correlation operations.
Solution Approach 2:
The hierarchical structure acts as an intermediary layer between raw text strings and final calendar schedule generation. Instead of directly correlating distributed date elements, the system first maps them to hierarchical nodes that represent their contextual relationships. This intermediary hierarchical representation simplifies the correlation process by providing a structured framework that naturally captures the relationships between partial date elements.
Data Source
AI summary
Systems and methods for automatically detecting date information in electronic documents. In some embodiments, a media guidance application may automatically associate a first partial calendar date-and-time indicator to a second partial calendar date-and-time indicator that appears at a separate location in a document. The media guidance application may determine whether the partial calendar date-and-time indicators are correlated, and then combine the partial calendar date-and-time indicators to obtain a complete date-and-time representation.