SEO Research Suite database: Hundreds of SEO and LLMO related papers and patents (Google, Microsoft, OpenAI) ... every SEO should know!
Here you can find a database of hundreds of search related active patents and papers. The patents and papers are tagged by SEO and LLMO/GEO related topics, steps of the information retrieval process and the probabilty they could be used nowadays or in the future.
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Insights of hundreds active Microsoft, OpenAI and Google patents and resesearch papers about how search engines and LLMs work.
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Google patents and research papers summarized from a SEO / GEO perspective.
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All patents tagged by topic and important authors for quick and targeted research.
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A patent application does not mean that the methods described there will find its way into practice in the search engines. An indication of whether a methodology/technology is so interesting for Google that it could find its way into practice can be obtained by checking whether the patent is pending only in the US or other countries. The claim for a patent priority for other countries must be made 12 months after the first filing.Regardless of whether a patent finds its way into practice, it makes sense to deal with Google patents, as you get an indication of the topics and challenges that product developers at Google and other search engines are dealing with.
This Google patent describes a method for generating content labels, such as titles or hashtags, for a topic based on user search queries. The process involves retrieving terms associated with read more
This Micorosoft patent describes a method for managing indexed data to enhance content retrieval, particularly when dealing with large datasets. It introduces techniques like generating and managing data shards to read more
This document introduces a new method called Direct Reasoning Optimization (DRO), which is designed to improve how large language models (LLMs) perform on tasks that are more creative and open-ended. read more
The patent describes systems and methods designed to provide users with reliable, expert-verified information. When a user submits a query, the system identifies the specific field of expertise, searches a read more
This Microsoft patent describes a method for training a large language model (LLM) to convert natural language queries into structured search queries. It involves using one LLM to generate natural read more
The Microsoft patent focuses on a system and methodology that leverages indexing of content to enhance the efficiency of content retrieval, especially when handling extensive data sets in multi-tenant scenarios. read more
The Microsoft patent describes a system and method for enhancing natural language understanding by integrating a language module with a knowledge module. This is achieved through the multi-alignment of two read more
The Google paper explores the theoretical limitations of embedding-based retrieval systems in information retrieval (IR). It highlights that while vector embeddings are widely used for various complex retrieval tasks, they read more
The OpneAI patent presents a methodology for enhancing user interactions with a generative response engine during long-running tasks. Unlike traditional systems that restrict user engagement until task completion, this patent read more
The Google patent details a method for enhancing the responses generated by a large language model (LLM) to user queries by utilizing a custom corpus of documents. It involves receiving read more