Entity Information Discovery via Email Domain Analysis
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Solution Overview
Problem
Conventional methods face difficulties in obtaining actionable information about smaller, private entities due to sparse online data, making it challenging to acquire reliable information using only an entity name or email address.
Innovation Solution
An improved technique that generates a URL from starting data, downloads content from a website, and analyzes it to produce entity-specific information along with a confidence score, which can also involve accessing public databases and social networking websites to validate or acquire additional information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional search methods are used to obtain information about entities, then information about large publicly traded corporations can be obtained, but information about smaller private entities is sparse or unavailable
Solution Approach 1:
The patent uses email addresses as intermediary data to bridge the gap between having minimal starting information and accessing entity information. By extracting domain names from email addresses and using them to generate website URLs, the system creates a pathway to obtain information about private entities that conventional search methods cannot access directly
Solution Approach 2:
The patent transitions from traditional search dimensions (entity names, keywords) to a new dimension (email domain names) for accessing entity information. This dimensional shift enables retrieval of information about private entities by leveraging the structure of email addresses rather than relying on publicly available entity names or descriptions
2Loss of information
If automated URL generation and website analysis is performed to obtain information about private entities, then entity-specific information can be retrieved, but the complexity of the system increases
Solution Approach 1:
The patent segments the information retrieval process into distinct modular steps: receiving starting data, extracting email domain names, generating URLs, downloading website content, and analyzing the content. This segmentation allows each component to be independently implemented and maintained, reducing overall system complexity while enabling comprehensive information retrieval about private entities
3Loss of information
If information is obtained from sparse online data about private entities, then some entity information can be acquired, but the reliability and accuracy of the information decreases
Solution Approach 1:
The patent implements feedback mechanisms where the system analyzes website content to extract entity-specific information and validates findings by cross-referencing multiple data points from the website. This feedback loop allows the system to assess the reliability of obtained information and adjust its analysis approach accordingly, improving accuracy even when starting with sparse data about private entities
Data Source
AI summary
A technique for acquiring information about entities includes receiving starting data including an entity name and/or email address, generating a URL (Uniform Resource Locator) from the starting data, and downloading content from a website at the generated URL. Downloaded content from the website is analyzed to generate a set of entity-specific information and a confidence score. The confidence score specifies a likelihood that the entity-specific information pertains to the same entity that was described in the starting data. Using the improved technique, persons are able to obtain information about entities, even small, private entities about which information online is sparse, along with a measure of quality of the information obtained.