Method for accelerated long document search using Hilbert curve mapping
US12130790B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 22, 2024 |
| Grant date | Oct 29, 2024 |
| Priority date | — |
| Expiry date | Jan 22, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/953
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method includes a textual document search engine. The method initializes the textual document search engine by inputting, into a memory, a very large number of documents, where each document has textual sentences, and each sentence of each document has m semantic embedding vectors. The method maps the m semantic embedding vectors to 1-dimensional vectors of Hilbert numbers using a Hilbert curve transformation, constructs an index table with the 1-dimensional vectors, and stores the index table in the memory. The index table is used for efficient search by inputting a full query document, which has embedding vectors corresponding to sentences in the query document, where the query embedding vectors are mapped into 1-dimensional vectors of Hilbert numbers using Hilbert curve transformation. The index table is searched using the Hilbert numbers and candidate documents are retrieved that are similar to the query document based on the Hilbert numbers.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.