Intent-Based Media Search Using Contextual Inference
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Solution Overview
Problem
Conventional media file search systems fail to provide relevant results as they only rely on user-submitted search terms, neglecting the user's intent and context, leading to less relevant content being returned.
Innovation Solution
An intent-based search system that infers user intentions by utilizing additional information such as geographic location, language settings, and prior search history to prioritize search results, enhancing relevance by considering user context during media file searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search systems only use user-submitted search terms, then the search system remains simple and fast, but the relevance of search results deteriorates
Solution Approach 1:
The system pre-collects and stores user context information (location, language settings, search history) before search queries are submitted. This preliminary data gathering enables the search system to automatically infer user intent without requiring users to explicitly provide it, thereby improving result relevance while maintaining relatively simple user interaction
Solution Approach 2:
The patent introduces an intermediary component that analyzes user context data and infers search intent, acting as a bridge between the simple search query interface and the complex relevance ranking process. This intermediary layer processes contextual information to generate intent signals that enhance result relevance without requiring the entire system to become fundamentally more complex
2Measurement precision
If the search system collects additional user context information, then the accuracy of intent inference improves, but the amount of data processing and storage requirements increase
Solution Approach 1:
The system extracts only the most relevant contextual features (location, language, recent search patterns) from the available user data, discarding redundant information. This selective extraction maintains high intent inference accuracy while minimizing the volume of data that needs to be processed and stored
Solution Approach 2:
Different levels of contextual analysis are applied based on the specific search context and user profile. For some users or search types, more detailed contextual analysis is performed, while for others, simpler analysis suffices. This localized approach to data processing optimizes the balance between inference accuracy and processing overhead
Data Source
AI summary
In a computer-implemented method for performing intent-based search of media files, a search query for searching media files of a library of media files is received from an electronic device. The search query includes a user-entered search term and additional search information related to an intent of a user. The library of media files is searched for media files according to the search query. Search results are returned to the electronic device, the search results including a listing of media files satisfying the user-entered search term and prioritized according to the additional search information related to the intent of the user.