System and Method for Rapid Relevant Data Retrieval from an Electronic Knowledge Base
AssigneeAcurai, Inc.
InventorMichael Wood
Life of this patent
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Abstract
Intelligent Storage and Retrieval (ISAR) systems and methods are described, which combine keyword search methods with vector search methods. ISAR also includes additional sub-systems and methods such as ngram searching, entity counts, hyponym filtering, and selective synonym expansion. ISAR pinpoints the exact passages that are relevant to a given query and returns the facts that are precisely relevant to a given query. Some embodiments send the relevant facts themselves in lieu of sending any text chunks. Moreover, ISAR is extremely cost effective. It is extremely fast as well.
Claims1
A system for storing and retrieving information from an electronic knowledge base, the system comprising:
- a computer and an associated memory;
- at least one electronic document;
- at least one process for splitting the at least one electronic document into at least one section;
- a vector generation process;
- a vector database that supports metadata filtering;
- a point ID generation process;
- a storage entity count process for determining a total number of unique references to at least one entity type in each at least one section;
- a retrieval entity count process;
- at least one query;
- and
- a query filter construction process;
- wherein the at least one process for splitting the document creates at least one section;
- wherein the vector generation process transforms the at least one section into a vector embedding;
- where the at least one section is input into the storage entity count process, which returns at least one entity type field along with a count value for the at least one entity type field;
- wherein the point ID generation process generates a unique ID;
- wherein the unique ID, vector embedding, and the entity type field and its count value are sent to the vector database for storage;
- wherein the at least one query is input into the retrieval entity count process, which returns at least one query entity type field along with a count value for the at least one query entity type field;
- wherein the at least one query is input into the vector generation process which returns a query vector;
- wherein the query filter construction process constructs a query filter that comprises prefiltering on the at least one query entity type field and its associated count value and the query vector;
- wherein the query filter is sent to the vector database;
- and
- wherein a response is received from the vector database.
Dependencies are inferred from the claim text.