Title

Metadata Based Figure Search Engine for US Patent User Interface

Description/Abstract/Artist Statement

Most online search engines support searching for text-based documents, such as web pages. In this project, we investigate an approach to build a search engine that allows users to search figures in patents. Besides keyword-based searching, the user interface (UI) offers a set of functionalities allowing users to tag, create customized lists, like patent figures, and perform advanced searches based on metadata of figures, such as patent ID, text reference, figure ID, aspect, and the object depicted in the figure. The metadata is queried by JSON objects that are indexed by the state-of-the-art search platform called Elasticsearch. The interface and functionality are implemented with HTML, CSS, JavaScript, PHP, AJAX, and MySQL. The UI was tested and the items in the search engine result page return relevant patent figures. Such UI can be used for building a large corpus of multi-labeled figures, which can further be used for training and evaluating computer vision models for automatic object recognition.

Presenting Author Name/s

Winston Shields

Faculty Advisor/Mentor

Jian Wu

College Affiliation

College of Sciences

Presentation Type

Poster

Disciplines

Databases and Information Systems | Graphics and Human Computer Interfaces | Software Engineering

Session Title

Engineering Research #1

Location

Zoom Room K

Start Date

3-20-2021 10:00 AM

End Date

3-20-2021 10:55 AM

This document is currently not available here.

Share

COinS
 
Mar 20th, 10:00 AM Mar 20th, 10:55 AM

Metadata Based Figure Search Engine for US Patent User Interface

Zoom Room K

Most online search engines support searching for text-based documents, such as web pages. In this project, we investigate an approach to build a search engine that allows users to search figures in patents. Besides keyword-based searching, the user interface (UI) offers a set of functionalities allowing users to tag, create customized lists, like patent figures, and perform advanced searches based on metadata of figures, such as patent ID, text reference, figure ID, aspect, and the object depicted in the figure. The metadata is queried by JSON objects that are indexed by the state-of-the-art search platform called Elasticsearch. The interface and functionality are implemented with HTML, CSS, JavaScript, PHP, AJAX, and MySQL. The UI was tested and the items in the search engine result page return relevant patent figures. Such UI can be used for building a large corpus of multi-labeled figures, which can further be used for training and evaluating computer vision models for automatic object recognition.