Search Processing Platform Using Learned Model for User Input History
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face difficulties in inputting suitable search conditions for applications, especially when past and unknown information are sought, as they may not have suitable image data or search words, leading to cumbersome operations.
Innovation Solution
An information processing apparatus with a platform that uses a learned model to estimate search data from user input history, including operations on connected devices, to provide search results without requiring explicit search conditions from the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a photographic image is input to obtain a search result using machine learning, then the search can be executed, but the user cannot input suitable search conditions in some cases and may not have suitable image data
Solution Approach 1:
The system automatically executes search processing by utilizing operation history data without requiring the user to manually input search conditions. The estimation processing autonomously determines appropriate search parameters based on past user behavior, eliminating the need for users to provide image data or formulate search queries themselves.
Solution Approach 2:
The system pre-collects and stores operation history data including user inputs and device operations before search execution. This preliminary data collection enables the estimation processing to generate appropriate search conditions automatically when the user initiates a search, eliminating the need for real-time condition specification.
2Productivity
If the user sets information associated with previous words and actions as search conditions after application activation, then the search can be conducted, but the operation becomes complicated
Solution Approach 1:
The estimation processing automatically generates search conditions by analyzing operation history data, eliminating the need for users to manually configure search parameters. The system self-determines appropriate search terms and settings based on collected user behavior data, reducing operational complexity while maintaining search effectiveness.
Solution Approach 2:
The system extracts relevant search conditions from operation history data automatically, separating the complex task of search condition formulation from the user. Only essential user actions (permitting estimation processing and executing search) are required, while the complex intermediate step of condition setting is extracted and handled automatically by the system.
3Extent of automation
If the application uses operation history data for estimation processing, then automatic search condition generation is enabled, but user permission and data handling complexity increase
Solution Approach 1:
The system implements a permission feedback mechanism where the user grants authorization for estimation processing to access operation history data. This feedback loop ensures user control while enabling automation, as the system only processes data with explicit user permission, balancing automation extent with user privacy and control.
Data Source
AI summary
In an information processing apparatus having a platform supporting estimation processing using a model that has learned a relationship between data associated with user word and action and information to be used for search processing, in a case where the estimation processing is executed by using input data based on user input performed before usage of an application and the model, and an output estimation result is recorded, the application acquires the estimation result from the platform, executes search processing using information included in the estimation result, and provides the information using the result.