Key Phrase Validation for Search Document Positioning
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Solution Overview
Problem
Conventional search engines are ineffective in accurately correlating electronic documents to hierarchical topic maps, leading to irrelevant document positioning, as they rely on keyword strategies that may not align with the document's content, causing poorly correlated documents to be lost despite their actual relevance.
Innovation Solution
The implementation of a quotient matrix and correlation coefficient system within an information handling system to automatically generate and validate key phrases, determining their relevance by calculating a ratio of key phrases to total words and measuring correlation with other documents, thereby optimizing metadata for better search engine optimization (SEO) and positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional keyword-based search strategies are used, then search engine implementation is simple, but document positioning accuracy deteriorates leading to irrelevant document positioning
Solution Approach 1:
The system performs preliminary extraction of key phrases from electronic documents before search operations. By pre-processing documents to identify and extract meaningful key phrases (rather than relying on simple keywords), the system prepares structured data that enables more accurate positioning without increasing operational complexity during actual search execution.
Solution Approach 2:
The patent introduces an intermediary validation mechanism that correlates extracted key phrases with hierarchical topic maps. This intermediary layer acts as a mediator between raw document content and search results, validating whether key phrases accurately represent document topics before positioning documents in search results, thereby improving accuracy without requiring complete system redesign.
2Reliability
If keyword-based correlation is used, then processing speed is maintained, but document-relevance identification deteriorates causing relevant documents to be lost
Solution Approach 1:
The system applies partial action by focusing key phrase extraction and validation only on the most relevant portions of documents rather than processing entire documents uniformly. By concentrating computational resources on extracting and validating key phrases (rather than analyzing all text), the system improves relevance identification while maintaining acceptable processing efficiency through selective rather than exhaustive analysis.
Solution Approach 2:
The patent segments the document processing task into distinct phases: key phrase extraction, validation against topic maps, and correlation scoring. This segmentation allows each phase to be optimized independently, improving overall reliability of relevance identification while managing computational complexity through divided processing steps rather than monolithic analysis.
3Measurement precision
If manual indexing and crawling optimization is performed, then search accuracy improves, but labor costs and time consumption increase
Solution Approach 1:
The system implements self-service through automated key phrase extraction and validation mechanisms that operate without manual intervention. The automated system extracts key phrases from documents, validates them against hierarchical topic maps, and generates correlation coefficients automatically, eliminating the need for manual indexing while maintaining high search accuracy through algorithmic rather than human processing.
Solution Approach 2:
The patent replaces manual mechanical indexing processes with automated computational mechanisms. Instead of human indexers manually analyzing and categorizing documents, the system uses algorithmic key phrase extraction, validation, and correlation scoring to automatically position documents in search results, substituting human labor with automated processing that achieves comparable or superior accuracy without time loss.
Data Source
AI summary
Online search retrieval is improved by automatic generation of key phrases. When a search engine crawls an electronic document, key words and phrases greatly help organize the electronic document to one or more topics. A quotient matrix defines a ratio of a key phrase to a total number of words in the electronic document. A correlation coefficient may also determine which key phrase correlates to the electronic document. A title key phrase may then be generated in response to the correlation coefficient having a positive value. When the search engine crawls the electronic document, the title key phrase may be provided as metadata.