Multimedia Search Personalization via Cached Concept Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional search engines for multimedia content are limited in optimizing results based on user preferences and are restricted to indexed images and web pages, failing to provide optimized recommendations for multimedia content beyond web displays.
Innovation Solution
A method and system that utilize a deep content classification engine on user devices to match input multimedia content with cached concepts, generate signatures, and perform searches across data sources to retrieve relevant multimedia content items, filtering results based on user characteristics for optimized content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional search engines index and search only images and web pages, then the search scope is limited but the system complexity is low, but the adaptability and versatility of the search system deteriorates
Solution Approach 1:
The search system is extended to handle multiple types of content including images, web pages, email messages, documents, and other data items. The indexing and search mechanisms are designed to work across diverse content types, making the system universal and multi-functional rather than limited to specific formats.
Solution Approach 2:
The search system is divided into separate components: an indexing component that processes and indexes content from multiple sources, a search component that handles queries, and a recommendation component that provides personalized results. This segmentation allows the system to manage complexity through modular design while maintaining versatility.
2Adaptability or versatility
If search engines provide recommendations based only on webpage context, then the implementation is simple but the personalization and user preference optimization deteriorates
Solution Approach 1:
The system incorporates user feedback mechanisms where user interactions with search results and recommendations are tracked and used to refine future recommendations. This feedback loop enables personalization by adapting to individual user preferences while maintaining a manageable level of complexity through iterative improvement rather than complex upfront design.
Solution Approach 2:
The system performs preliminary indexing and categorization of content from multiple sources before search is needed. User profiles and preferences are pre-configured and updated based on past behavior. This preliminary action reduces the complexity of real-time personalization by preparing data structures and user models in advance.
Data Source
AI summary
A method for conducting search-by-content is provided. The method includes responsive to an input multimedia content item provided to a user device, checking if the input multimedia content item matches at least one concept of a plurality of concepts cached in the user device; retrieving characteristics set for a user of the user device; performing a search, using the at least one matching concept, for multimedia content items similar to the input multimedia content item; determining which of the search results are of interest to the user based on the characteristics set for the user; and saving results that are of interest to the user in the user device, wherein the saved results include multimedia content items.