Context-Aware Multimedia Retrieval for Trending Topics
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Solution Overview
Problem
Current search systems fail to effectively identify multimedia content relevant to trending topics, often returning unrelated results due to a lack of context-based filtering, leading to user dissatisfaction.
Innovation Solution
A system and method that process user inputs as search queries, extract content from social media, generate keywords based on context, prioritize them using affinity and occurrence scores, and construct expanded queries to identify relevant multimedia content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a user searches the internet with a word or phrase related to the trending topic, then the search system can retrieve multimedia content, but the retrieved content is huge and may not relate to the context associated with the trending topic
Solution Approach 1:
The search query is segmented into the trending topic keyword and extracted context keywords from social media content. The context extracting module identifies relevant keywords from social media posts, and the query generating module combines these segmented parts into an expanded query that maintains both the trending topic and its contextual meaning, thereby filtering out irrelevant content while preserving quantity.
Solution Approach 2:
Social media content acts as an intermediary source that provides contextual information about the trending topic. The context extracting module uses this intermediary content to generate keywords that bridge the gap between the trending topic and relevant multimedia content, enabling precise retrieval without losing volume.
2Ease of operation
If a typical search system identifies multimedia content by matching the word with existing content, then the search process is simple, but the multimedia content identified may include content unrelated to the context associated with the trending topic
Solution Approach 1:
The system performs preliminary action by extracting and analyzing social media content before executing the actual search. The context extracting module processes social media posts in advance to identify relevant keywords and context, which are then used to formulate an expanded query. This preliminary contextual analysis ensures reliable relevance without significantly complicating the overall search operation.
Solution Approach 2:
The search query parameters are changed by expanding the simple keyword match into a composite query that includes both the trending topic and context keywords. This parameter transformation from simple to expanded query maintains operational simplicity while dramatically improving reliability through context-aware filtering.
Data Source
AI summary
A system for identifying one or more multimedia content relevant to a trending topic is provided. The system includes a display unit, a memory unit that stores a set of modules and a database, and a processor that executes the set of modules. The set of modules include a query processing module, a content extracting module, a context extracting module, and a multimedia content identifying module. The query processing module processes a user input including a search query. The content extracting module extracts content which corresponds to the search query from a social medium. The context extracting module includes a) a keyword generating module obtains one or more generated keywords from the content, and b) a keyword qualifying module obtains one or more keywords from the one or more generated keywords. The multimedia content identifying module identifies the one or more multimedia content based on the one or more keywords.