Semantic Search Engine for User Generated Content
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Solution Overview
Problem
Current search engines for user-generated content face challenges in providing meaningful and efficient search results, as they often yield too literal matches, yield single data points, are overwhelmed by excessive reviews, and fail to uncover related information, making it difficult for users to aggregate and contextualize data effectively.
Innovation Solution
A computer-implemented method and system that processes user-generated content by categorizing substrings using dictionaries or pattern analysis, assigning sentiment and influence indicators, and displaying relevant content, enabling a semantic search engine to provide aggregated and contextualized results across multiple domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional keyword-based search is used, then search speed and simplicity are improved, but search accuracy and meaningful results deteriorate
Solution Approach 1:
The patent transforms the search parameter from simple keyword matching to multi-dimensional semantic analysis. It introduces sentiment scores, influence metrics, and concept categorization as new parameters for evaluating and ranking search results, enabling the system to understand user intent beyond literal keyword matches.
Solution Approach 2:
The patent introduces an intermediary processing layer between the user query and the search results. This layer includes sentiment analysis engines, concept extraction modules, and influence calculation systems that mediate between the raw search request and the final results, adding semantic understanding without significantly increasing user-perceived search time.
2Loss of information
If all individual reviews are displayed, then completeness of information is improved, but user experience and ease of operation deteriorate
Solution Approach 1:
The patent merges multiple individual reviews into aggregated summaries that preserve essential information while reducing volume. It combines sentiment analysis results, influence metrics, and key theme extraction to create condensed representations that maintain information completeness while improving readability and user experience.
Solution Approach 2:
The patent segments the overwhelming mass of reviews into organized categories based on sentiment, topic, and influence. By dividing reviews into meaningful groups with representative summaries, it allows users to navigate information systematically rather than being overwhelmed by unstructured individual opinions.
3Measurement precision
If semantic processing and categorization are applied, then search accuracy and insight quality are improved, but system complexity and processing time worsen
Solution Approach 1:
The patent performs preliminary semantic processing and categorization during the content ingestion phase rather than during user queries. By pre-computing sentiment scores, influence metrics, and concept categorizations for all user-generated content, it reduces the complexity of real-time search processing while maintaining high search accuracy.
4Loss of information
If comprehensive analysis of all content is performed, then discovery of relevant information is improved, but processing time and computational resources worsen
Solution Approach 1:
The patent applies partial analysis by focusing computational resources on the most influential and relevant content based on pre-calculated influence metrics. Rather than uniformly analyzing all content, it prioritizes high-influence reviews and uses sampling strategies for less critical content, achieving comprehensive information discovery with reduced processing time.
Data Source
AI summary
A method and system for a search engine for user generated content have been disclosed. According to one embodiment, a computer implemented method comprises receiving a search request from a client, the search request directed to user generated content. Relevant user generated content is retrieved, wherein retrieving comprises searching processed user generated content, and wherein processing user generated content comprises receiving first input data including text, creating a substring of text from the first input data and categorizing the substring to produce a concept associated with the substring, wherein the substring is categorized according to one of dictionaries or pattern analysis. An indication of sentiment is assigned to the concept associated with the substring and an indication of influence is assigned to the concept associated with the substring. The relevant user generated content is displayed.