Contact Disambiguation via Graph Relationship Data
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Solution Overview
Problem
Existing contact information retrieval tools face difficulties in disambiguating contacts with similar names or attributes from large databases, leading to inefficiencies and increased computational resource usage.
Innovation Solution
A contact system utilizing relationship data to identify candidate contacts through a virtual assistant, employing a graph database service to search for contacts based on attributes like project, team, or role, and limiting the number of candidates presented to the user for selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a user searches for contact information in a large contact database using traditional tools, then the search can access all contacts, but the time and computational resources required increase significantly when there are many contacts with similar names
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing relationship data between contacts in a graph database structure. When a search is initiated, the system has already organized contact relationships (such as frequent interactions, professional connections, communication patterns) in advance, allowing for rapid retrieval of relevant contacts without computing these relationships in real-time during the search process
Solution Approach 2:
The patent introduces relationship data as an intermediary layer between the contact database and the search query. This relationship data acts as a mediator that filters and ranks contacts based on their relational proximity to the user, thereby reducing the search space and improving both accuracy and speed without requiring the user to manually evaluate all contacts
2Measurement precision
If traditional contact search tools return all matching contacts, then completeness is maintained, but the number of irrelevant contacts increases, reducing precision
Solution Approach 1:
The system applies local quality by differentiating contacts based on their individual relationship strengths with the user. Instead of treating all contacts uniformly, the patent assigns different relevance scores to contacts based on localized relationship attributes (such as frequency of interaction, recency, professional relationship type), allowing the system to prioritize and present only the most relevant contacts while filtering out less relevant ones
3Reliability
If the system searches through a large contact database without optimization, then all potential contacts are considered, but computational resources are wasted on irrelevant contacts
Solution Approach 1:
The patent segments the contact database into meaningful groups based on relationship data, such as frequent contacts, professional contacts, and occasional contacts. This segmentation allows the search algorithm to focus computational resources on relevant segments first, rather than uniformly processing the entire database, thereby maintaining completeness while reducing overall computational expenditure
Data Source
AI summary
Technologies are disclosed for disambiguating contact information using relationship data using a virtual assistant. A user interacts with a virtual assistant to obtain and utilize contact information. For example, a virtual assistant may allow users to perform an action that utilizes contact information (e.g., make a call to a contact). The virtual assistant utilizes a contact service to identify candidate contacts that are related to the requesting user. The contact service identifies candidate contacts based on relationship data between the requesting user and the stored contacts. For example, the relationship data may indicate that the requesting user is on the same project or team as another contact, that the requesting user has the same role as another contact, that the requesting user is a manager of another contact, as well as other attributes. In some examples, the contact service limits the number of candidate contacts provided to requesting user.