Text Scoring via Internal Theme Analysis
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Solution Overview
Problem
Conventional search engines rely on external information, such as hyperlinks, to rank webpages, which can lead to inaccurately determining the importance or value of a webpage, especially when few or no external links exist, resulting in less relevant search results.
Innovation Solution
A computer-implemented method and system that scores text based on internal information, such as themes, their frequency, distribution, and location within the text, to determine the importance or value of webpages, reducing reliance on external information for ranking and filtering search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search engines use external information (hyperlinks) to rank webpages, then the ranking process is simple and fast, but the accuracy of determining webpage importance deteriorates when external links are scarce or non-existent
Solution Approach 1:
The patent segments the text into multiple portions and identifies themes within each portion separately. By dividing the text analysis into thematic segments rather than treating the entire text as a single unit, the system can more accurately assess the importance of different content areas, thereby improving the precision of webpage importance determination without requiring complex external link analysis
Solution Approach 2:
The patent introduces themes as intermediary elements that connect search queries to webpage content. Instead of directly comparing external links to determine importance, the system uses theme identification as an intermediary step - matching query themes with webpage themes to assess relevance and importance. This intermediary approach improves accuracy while maintaining system manageability
2Reliability
If conventional search engines rely on external links for ranking, then the system is easy to implement, but it fails to return relevant results when important documents have few or no external links
Solution Approach 1:
The patent enables webpages to self-assess their own importance through internal theme analysis rather than relying on external validation via hyperlinks. The system identifies themes within the webpage content itself, allowing the text to serve its own ranking purpose. This self-service approach ensures that important documents are reliably identified based on their intrinsic content quality rather than external link popularity
Solution Approach 2:
The patent changes the ranking parameters from external metrics (number of hyperlinks) to internal metrics (theme frequency, theme distribution, theme location within text). By transforming the basis of evaluation from external link counts to internal thematic analysis parameters, the system achieves more reliable search results that reflect actual content importance rather than link popularity
3Measurement precision
If the system analyzes internal information (themes, frequency, distribution, location) to score texts, then the accuracy of importance determination improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent divides the text into multiple portions and analyzes themes within each segment separately. This segmentation allows the system to process large texts in manageable chunks, identifying themes, their frequencies, distributions, and locations incrementally rather than analyzing the entire text at once, thereby reducing processing time while maintaining scoring precision
Solution Approach 2:
The patent applies partial action by focusing theme analysis on specific portions of the text rather than requiring complete analysis of every single word or character. The system identifies key themes and their distributions in representative portions, which is sufficient to determine overall text importance without the excessive time cost of exhaustive analysis
Data Source
AI summary
A computer-implemented method, computer-readable medium and system for scoring a text are disclosed. Themes within one or more texts may be determined and used to score each text, where an overall score for each text may indicate a respective importance and/or value of each text. The score for each text may be determined based upon a number of themes, type of themes, frequency of theme elements associated with the themes, distribution of theme elements associated with the themes, location of themes in the text, some combination thereof, etc. In this manner, the importance or value of one or more texts may be determined more accurately using information within each text with reduced reliance upon external information. Additionally, more relevant search results can be returned to a user by using internal information to perform ranking operations and/or filtering operations associated with a search.