Client Query Routing via Keyword Classification
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Solution Overview
Problem
Entities face challenges in accurately identifying the originator of client queries and routing them to the appropriate location within the organization, as queries often lack clear identification of the sender and may not include necessary information, leading to misplacement and delayed handling.
Innovation Solution
A client case management system that receives client queries, extracts origination identification data, searches query history, compares character strings against a classification model to identify the sender, and routes the query to the appropriate sub-entity based on keywords and attributes, using a combination of machine learning and database searches to determine the correct recipient.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification and routing of client queries is performed, then flexibility in handling diverse queries is maintained, but accuracy in identifying senders and routing efficiency deteriorates due to lack of clear identification data
Solution Approach 1:
The system enables automatic self-identification of query senders by extracting identification data from query metadata (email addresses, IP addresses, device identifiers) and autonomously routing queries to appropriate sub-entities based on keyword matching and classification models, eliminating the need for manual identification while improving both accuracy and efficiency
Solution Approach 2:
The patent replaces manual mechanical processes of query identification and routing with automated computational systems including data extraction algorithms, database search mechanisms, classification models, and automated routing logic that process queries based on extracted identification data and keyword analysis
2Reliability
If automated extraction and analysis of query data is implemented, then routing accuracy improves through precise sender identification, but system complexity increases due to multiple processing steps
Solution Approach 1:
The system segments the query processing task into distinct modular components: data extraction module that retrieves identification data from queries, search module that queries databases for sender information, classification module that analyzes keywords and determines query type, and routing module that directs queries to appropriate sub-entities. This segmentation manages complexity by organizing functions into separate, manageable units
Solution Approach 2:
The system employs universal data structures and processing mechanisms that handle multiple query types and identification data formats through a single integrated framework. The classification model and routing logic serve multiple functions by processing diverse queries uniformly, reducing the need for separate specialized systems
Data Source
AI summary
A method for managing and routing client queries within an entity is provided. The method may include receiving a client query including origination identification data associated with a sender of the client query. In response to searching in a database for history correlating to the origination identification data, determining that no relevant history exists with respect to the origination identification data. The method may include identifying the sender by identifying, within the query, a first character string identical to a first keyword stored in a classification model within a database, using the first keyword to identify a second character string that includes the first keyword in addition to other characters, identifying, from a list of sub-entities, a sub-entity associated with the first keyword and using a combination of the first keyword, the sub-entity and one or more attributes to identify the sender as an existing client.