Contact Information Extraction via Prominence Scoring
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Solution Overview
Problem
Existing technologies in computerized content delivery networks struggle to efficiently extract and associate contact information from resources with content items, leading to incomplete or inaccurate presentation of contact details to users.
Innovation Solution
A computer-implemented method and system that receive a content item and URL from a content provider, load the identified resource, detect multiple contact information, calculate prominence scores for each, select the most prominent contact information, and associate it with the content item.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If contact information is extracted from resources in content delivery networks, then user accessibility to contact details improves, but the complexity of information extraction and association increases
Solution Approach 1:
The patent extracts contact information from resources using automated detection mechanisms. The system identifies and separates contact details (phone numbers, email addresses, physical addresses) from the resource content, then associates them with corresponding content items. This extraction process automates what would otherwise require manual effort, improving ease of operation while managing complexity through systematic processing.
Solution Approach 2:
The patent introduces an intermediary system that acts as a bridge between resources and content items. This intermediary automatically detects contact information, calculates prominence scores, and performs association operations. By inserting this intermediary layer, the system manages the complexity of extraction and association tasks while providing simplified access to users.
2Quantity of substance
If multiple contact information are detected from a resource, then completeness of contact information improves, but difficulty in selecting the most relevant contact information increases
Solution Approach 1:
The patent changes the parameter of contact information by introducing a prominence score. This score is calculated based on various factors such as the contact information's position in the resource, its formatting, and its relevance to the content item. By transforming contact information into scored data, the system automatically identifies the most relevant contact details without manual intervention, resolving the selection difficulty while maintaining completeness.
3Measurement precision
If automated prominence scoring is implemented for contact information, then accuracy of contact information selection improves, but processing time and computational resources increase
Solution Approach 1:
The patent implements prominence scoring that focuses on key determining factors rather than analyzing every possible attribute of contact information. The scoring mechanism evaluates essential parameters (such as position, format, and contextual relevance) to generate accurate selections within acceptable timeframes. This partial action approach maintains measurement precision while reducing unnecessary computational overhead.
Data Source
AI summary
Systems and methods for automatically extracting a plurality of contact information from a resource, calculating prominence scores of each contact information, and associating a selected contact information with a content item are provided. A content item and a uniform resource locator are received from a content provider. A resource identified by the uniform resource locator is loaded. A plurality of contact information is detected from the loaded resource. For each of the detected contact information, a prominence score is calculated. One of the plurality of contact information is selected based on the calculated prominence scores. The selected contact information is associated with the content item.