Keyword Research Knowledge Graphs for Faster SEO Topic Discovery
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Solution Overview
Problem
Existing methods for search engine optimization (SEO) are cumbersome and time-consuming, providing minimal beneficial effect on organic visibility and traffic of web pages.
Innovation Solution
A tool that utilizes an ensemble of key phrase extraction, graph analysis, and natural language processing algorithms to identify semantically relevant topics for SEO, generating a knowledge graph and outputting a ranked list of topics based on relevance scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual keyword research is performed, then SEO effectiveness is improved, but time consumption increases
Solution Approach 1:
The system performs keyword research and topic identification automatically without requiring manual intervention. The automated crawler retrieves web content, the ensemble of algorithms processes the data, and the system generates ranked topic lists independently, eliminating the need for manual keyword research while maintaining SEO effectiveness
Solution Approach 2:
The patent replaces manual mechanical keyword research processes with an automated computational system. The ensemble of algorithms (including Bayesian statistical ensemble, graph analysis algorithms, and natural language processing algorithms) substitutes for human manual analysis, automatically extracting key phrases and generating SEO recommendations
2Productivity
If automated algorithms are applied to web content, then topic identification efficiency is improved, but system complexity increases
Solution Approach 1:
The patent combines multiple different algorithms (Bayesian statistical ensemble, graph analysis algorithms, natural language processing algorithms) into a unified ensemble system. By merging these algorithms and presenting them as an integrated topic identification system, the patent achieves high productivity while managing complexity through consolidation rather than separate complex subsystems
Solution Approach 2:
The ensemble of algorithms serves multiple functions within a single system: it performs key phrase extraction, topic identification, relevance scoring, and keyword generation. This multi-functionality reduces the need for separate specialized tools, thereby improving efficiency while the unified structure helps manage system complexity
Data Source
AI summary
In various embodiments, a method for generating from one or more keywords a list of related topics for organic search includes receiving, by a topic tool, an input of one or more keywords for which to generate a list of related topics. The method may further include acquiring, by a crawler, content from a plurality of different web content sources via one or more networks. The method may also include applying, by the topic tool, to the acquired content an ensemble of one or more key phrase extraction algorithms, one or more graph analyses algorithms and one or more natural language processing algorithms to identify a set of semantically relevant topics scored by relevance. The method may also include generating, by the topic tool, from the set of semantically relevant topics, a knowledge graph of related topics for the input of the one or more keywords. The method may further include outputting, by the topic tool based at least partially on the knowledge graph, an enumerated list of topics ranked by at least a relevance score.