Content Filtering via User Intent Data Clusters
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Solution Overview
Problem
Current electronic devices lack an effective mechanism to filter content based on user intent, leading to irrelevant search results due to the inability to accurately analyze and utilize user intent information for content retrieval.
Innovation Solution
The implementation of a mechanism in electronic devices that receives and processes data clusters containing user intent information, filters content accordingly, and displays relevant items, using techniques such as incremental latent Dirichlet allocation and latent semantic analysis to identify user interests and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search engines are used to retrieve content, then users can access a wide range of information, but the search results are often irrelevant to user intent
Solution Approach 1:
The system performs preliminary analysis of user intent information before content retrieval. Data clusters representing user interests are pre-generated and stored, allowing the system to quickly match user queries with relevant pre-analyzed data clusters, thereby improving search result relevance without losing user intent information
Solution Approach 2:
The patent introduces data clusters as an intermediary between user intent and content retrieval. These data clusters serve as a mediator that bridges the gap between raw user input and the vast information database, enabling more precise matching while preserving the nuances of user intent
2Measurement precision
If data clusters are used to filter content based on user intent, then search result relevance is improved, but system complexity increases
Solution Approach 1:
The system segments the vast information space into manageable data clusters based on user intent. By dividing content into organized clusters representing different user interests, the system achieves accurate content filtering without requiring complex processing of the entire information database at once
Solution Approach 2:
Data clusters are pre-generated and stored before actual content retrieval operations. This preliminary organization of information into intent-based clusters reduces the complexity of real-time processing while maintaining high filtering accuracy
Data Source
AI summary
An electronic device is provided. The electronic device includes a display, a communication circuit, and a processor electrically connected with the display and the communication circuit. The processor may be configured to display at least one data cluster containing user intent information on the display, select a data cluster to be applied to an application among the at least one data cluster according to a user input, filter at least one content or service among content and services available in the application on the basis of the selected data cluster, and display an item corresponding to the at least one filtered content or service on the display.