Dynamic Filter Controls for Content Item Filtering
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Solution Overview
Problem
Online merchants face challenges in providing an expedited and flexible search capability for users navigating through vast product catalogs, as existing methods rely on manually generated search indexes or curated collections, which are limited and static.
Innovation Solution
Implementing a system that dynamically determines filter controls based on attributes of content items, using user behavior data, user characteristics, and social network data to enable real-time filtering, allowing users to select filters that adapt to their preferences and interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manually generated search indexes or curated collections are used, then the search capability is simple to implement, but the filtering capability is limited and static
Solution Approach 1:
The patent implements dynamic filter controls that automatically adjust and update based on user behavior data, user characteristics, and social network data in real-time. The filtering capability evolves from static manual indexes to dynamic adaptive filters that respond to changing user preferences and interactions, resolving the contradiction between versatility and complexity by making the system adaptive rather than manually maintained
Solution Approach 2:
The system automatically generates and updates filter controls using user behavior data, user characteristics, and social network data without requiring manual intervention. The filtering system serves itself by autonomously adapting to user needs, eliminating the need for manual index generation while providing extensive filtering capability
Solution Approach 3:
The patent incorporates feedback loops where user interactions with content items are continuously monitored and used to refine and update filter controls. This feedback mechanism enables the system to learn from user behavior and improve filtering accuracy over time, balancing enhanced adaptability with automated processes that manage complexity
2Ease of operation
If dynamic filtering based on user data is implemented, then the user experience is enhanced, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing user behavior data, user characteristics, and social network data in structured formats. This preparation work is done in advance so that when filtering is needed, the system can quickly retrieve and apply relevant data without extensive real-time computation, reducing processing time while maintaining enhanced user experience
Solution Approach 2:
The patent applies filtering and data processing locally to specific user sessions and individual content items rather than globally processing all data. This localized approach processes only the necessary subset of data relevant to each user's current needs, minimizing processing time while still providing personalized enhanced user experience
Data Source
AI summary
Techniques are described for dynamically generating filter controls that enable the filtering of content items presented in a user interface such as a web application. In response to a request for content, one or more content items may be provided. The content item(s) may be analyzed to determine one or more attributes that describe the content item(s). The filter control(s) may then be determined dynamically based on the attribute(s) of the content item(s). The filter control(s) may be presented in the same user interface with the content item(s) to enable filtering of the content item(s) based on the attribute(s). The filter control(s) may be determined based on user behavior data, user demographic data, social network data, historical sales information, or other information.