Predicting user intent based on entity-type search indexes
US10614061B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 28, 2017 |
| Grant date | Apr 7, 2020 |
| Priority date | — |
| Expiry date | Mar 31, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/248
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An online system stores objects that may be accessed by users. The online system also stores indexes of terms related to different entity types of objects. When a user provides a search query, the online system compares the search terms with terms stored in the indexes. Based on the comparisons, the online system determines term features for entity types associated with an index. The online system provides the term features as inputs to a machine learning model. The machine learning model outputs a score for each entity type indicating a likelihood that the search query is for an object associated with the entity type. The machine learning model output is used by the online system to select one or more entity types that the user is likely searching for. The online system offers objects of the likely entity types to the user as results of the search query.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.