Predictive Search via Local Topic Maps
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Solution Overview
Problem
Current knowledge management systems face delays and inefficiencies due to the need for complete search queries, which result in wasted time and increased costs, especially in high-latency environments and peak usage periods, and fail to leverage recurring user patterns.
Innovation Solution
Implementing a system that allows partial entry of service requests, which queries a local topic map to provide matches before routing full queries to a search server, leveraging user profiles and topic maps to optimize search results and reduce network delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a complete search query is required before searching, then search results can be comprehensive, but user wait time increases and productivity decreases
Solution Approach 1:
The system performs preliminary actions by maintaining a local topic map that is pre-populated with categorized information before the user completes their search query. When the user enters partial text, the system immediately queries the local topic map to provide predictive matches, eliminating the need for the user to wait for a complete query to be processed before receiving results.
Solution Approach 2:
The search functionality is segmented into two independent parts: a local topic map for rapid predictive searching and a remote database for comprehensive results. This segmentation allows the system to handle partial queries locally without requiring complete query transmission to the remote server, thus improving user input speed while maintaining search result completeness.
2Measurement precision
If a complete query is sent to a remote server, then comprehensive search can be performed, but network delay increases
Solution Approach 1:
The search system is divided into a local component (topic map) and a remote component (database server). The local topic map handles predictive searching for partial queries, eliminating the need to transmit complete queries over the network. Only when local predictions are insufficient does the system send queries to the remote server, thereby reducing network transmission time while maintaining search result completeness.
Solution Approach 2:
The local topic map acts as an intermediary between the user and the remote database server. It processes partial queries locally and provides immediate predictive results, serving as a buffer that reduces the frequency and size of network transmissions to the remote server.
3Measurement precision
If a complete query is processed against an entire database index, then comprehensive search results are obtained, but server processing delay increases
Solution Approach 1:
The search processing is segmented into local processing (topic map query) and remote processing (database index search). The local topic map, which is pre-indexed and stored in memory, handles predictive searching for partial queries, eliminating the need to process complete queries against the entire remote database index. This reduces server processing time while maintaining search result completeness through the combination of local and remote search results.
Solution Approach 2:
The local topic map is pre-populated with categorized information before the user initiates a search. This preliminary action allows the system to immediately query and return predictive results for partial inputs without requiring the user to wait for comprehensive database processing.
4Measurement precision
If the user enters excessive data for a complete query, then search accuracy can be improved, but user time for data entry increases
Solution Approach 1:
The system performs preliminary actions by maintaining a pre-organized local topic map that categorizes information before the user completes their query. When the user enters partial text, the system immediately queries the local topic map to provide predictive matches, eliminating the need for the user to wait for or provide a complete query. This reduces user data entry time while maintaining search accuracy through intelligent predictions.
Solution Approach 2:
The system provides immediate feedback to the user in the form of predictive matches as they type, allowing the user to see potential results before completing their query. This feedback mechanism guides the user to provide only necessary information while maintaining search accuracy, reducing the time needed for data entry.
Data Source
AI summary
A partial entry of a service request is received into a service request window. Responsive to the receiving the partial entry of the service request, a first querying operation is performed on a first topic map. The first querying operation includes constructing a first query based on the partial entry. The first topic map is stored in conjunction with the application, and the application generates the service request window. Responsive to the performing the first querying operation, a first group of service request solution identifiers are retrieved. A result display is populated with the first group of service request solution identifiers. Responsive to a selection of a selected service request solution identifier from the result display, a service request solution associated with the selected service request solution identifier is retrieved. The service request window is populated with details derived from the service request solution.