Method and system of ranking and clustering for document indexing and retrieval
US7496561B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 1, 2003 |
| Grant date | Feb 24, 2009 |
| Priority date | — |
| Expiry date | Dec 25, 2025 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99935
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A relevancy ranking and clustering method and system that determines the relevance of a document relative to a user's query using a similarity comparison process. Input queries are parsed into one or more query predicate structures using an ontological parser. The ontological parser parses a set of known documents to generate one or more document predicate structures. A comparison of each query predicate structure with each document predicate structure is performed to determine a matching degree, represented by a real number. A multilevel modifier strategy is implemented to assign different relevance values to the different parts of each predicate structure match to calculate the predicate structure's matching degree. The relevance of a document to a user's query is determined by calculating a similarity coefficient, based on the structures of each pair of query predicates and document predicates. Documents are autonomously clustered using a self-organizing neural network that provides a coordinate system that makes judgments in a non-subjective fashion.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.