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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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.
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
The Google patent outlines a machine-learned system designed for personalizing sequence processing models by modeling user preferences using contextual data. It features an embedding model that generates embeddings representative of read more
The Microsoft patent describes a generative document system that utilizes large generative models (LGMs) to create interactive and comprehensive search result documents in response to user queries. The system dynamically read more
The Google patent describes a system that provides floating ranking for product search results in conjunction with general search results based on a user’s search query. It involves obtaining ranked read more
