Multidimensional Email Relationship Map for Analytical Querying
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Solution Overview
Problem
Existing methods for viewing email information are inefficient, as they require manual sorting and analysis of emails to extract relevant data, making it difficult to access and analyze essential information independently of email properties.
Innovation Solution
The system configures metadata for emails, creating a multidimensional relationship map that allows for querying and computing values based on attributes, rendering an analytical view of information through a relational data warehouse, facilitating decision-making by presenting data in a conceptual and accessible format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual sorting and analysis of emails is performed to extract relevant data, then essential information can be accessed, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by automatically configuring metadata and creating a relationship map from email attributes before any query is made. This pre-processing organizes email data into a structured multidimensional model, so when a user queries, the analysis is already prepared and can be quickly retrieved without manual sorting.
Solution Approach 2:
The patent introduces an intermediary analytical processing engine that acts as a mediator between the raw email data and the user. This engine automatically parses queries, identifies relevant emails using the pre-built relationship map, computes values for dimensions and measures, and renders analytical reports, eliminating the need for users to manually sort and analyze emails.
2Reliability
If all emails are accessed and analyzed to find relevant information, then complete data is available, but the complexity of the process increases
Solution Approach 1:
The patent segments the email analysis process into distinct modular components: metadata configuration, relationship map creation, query parsing, email identification, value computation, and report rendering. Each component handles a specific aspect of the analysis, making the overall complex process manageable and maintainable while ensuring complete data coverage through systematic processing.
Solution Approach 2:
The patent transforms the traditional flat email storage structure into a multidimensional analytical model with dimensions (categories, time periods, senders, recipients) and measures (email counts, response times, importance scores). This dimensional transformation allows complex queries to be answered by navigating along different dimensions rather than searching through all emails linearly, reducing process complexity while maintaining data completeness.
3Ease of operation
If emails are sorted to relevant folders to organize information, then access to specific emails is improved, but the flexibility to analyze from different perspectives is reduced
Solution Approach 1:
The relationship map serves as a universal structure that supports multiple analytical perspectives simultaneously. Instead of sorting emails into single-purpose folders, the system creates a multidimensional model where the same email data can be analyzed from various dimensions (time, sender, recipient, category, importance) without reorganizing the physical storage, providing both ease of access and analytical flexibility.
Solution Approach 2:
By organizing email attributes into a multidimensional relationship map rather than hierarchical folders, the system enables users to access emails through multiple dimensional lenses. A user can query by time period, sender, recipient, category, or any combination of dimensions, providing versatile analysis capabilities while maintaining easy access through the standardized metadata structure.
Data Source
AI summary
Described are methods and systems related to providing an analytical view of information present in one or more emails. Metadata of all the emails present in a mailbox is configured. The metadata includes an attribute of a corresponding email. Based upon the attributes of the emails, a relationship map is created. The relationship map is a multidimensional structure having multiple axes, with each axis describing an attribute of the emails. A query is received to query the mailbox. The query received is parsed to identify attributes of one or more relevant emails that are associated with the received query. A value is computed for each attribute of the relevant emails. Based upon the values computed for each attribute present in the relationship map, a resulting report having analytical view of information present in the relevant emails is rendered.