Semantic Crawler for User-Generated Content Analysis
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Solution Overview
Problem
The challenge lies in efficiently analyzing and presenting user-generated content across multiple websites with varying interfaces, as existing search engines struggle to extract relevant information due to high 'signal-to-noise' ratios and outdated indexing, making it difficult for users to find meaningful reviews quickly.
Innovation Solution
A method and system that collects, processes, and synthesizes user-generated content using a semantic crawler, sentence parser, and tokenizer to generate scores for core attributes, providing a customizable summary of sentiment and substance, enabling users to make informed decisions without reading through numerous reviews.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If user-generated content is collected from multiple websites, then the quantity of information increases, but the signal-to-noise ratio deteriorates making it difficult to find relevant content
Solution Approach 1:
The patent segments user-generated content into discrete sentences and further into individual words/tokens. This segmentation enables systematic analysis of each component, allowing the system to identify and extract meaningful information while filtering out noise through structured processing of sentence-level and word-level data
Solution Approach 2:
The patent introduces an intermediary semantic analysis system that acts as a mediator between raw user-generated content and final search results. This intermediary layer processes content through sentence parsing, tokenization, and semantic scoring to transform unstructured data into structured, searchable information with associated relevance scores
2Ease of operation
If traditional keyword search is used, then the ease of operation is maintained, but the measurement precision of search results deteriorates
Solution Approach 1:
The patent replaces traditional mechanical keyword-matching search with a semantic analysis system that uses sentence parsing, tokenization, and semantic scoring. This substitution transforms the search mechanism from simple string matching to intelligent semantic understanding, improving result precision while maintaining ease of use through natural language queries
3Loss of information
If user-generated content is aggregated from multiple sources, then the comprehensiveness of information improves, but the device complexity increases
Solution Approach 1:
The patent creates a universal processing system that handles multiple sources of user-generated content through a single integrated framework. The system performs sentence parsing, tokenization, and semantic scoring uniformly across diverse inputs, enabling comprehensive information aggregation without proportionally increasing complexity through standardized multi-functional processing
4Quantity of substance
If all user reviews are presented to users, then the quantity of information is maximized, but the loss of time increases making it difficult to make decisions quickly
Solution Approach 1:
The patent extracts key semantic elements and sentiment scores from large volumes of user-generated content, isolating the most relevant information. By extracting sentence-level meanings and word-level semantics, the system presents condensed, high-value information that maintains comprehensiveness while dramatically reducing the time needed for users to make informed decisions
Data Source
AI summary
A method and system for collecting and analyzing data found across multiple sites on the internet or stored in a self-contained or pre-loaded database, is disclosed which captures, extracts, analyzes, categorizes, synthesizes, summarizes and displays, in a customizable format, both the substance and sentiment embodied within user-generated content, such as comments or reviews, found across such sites and/or stored within such databases.