https://github.com/somefive/covid-19-search

A frontend website for a search engine designed for COVID-19 information.
https://github.com/somefive/covid-19-search

covid-19 information-retrieval search-engine

Last synced: 24 days ago
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A frontend website for a search engine designed for COVID-19 information.

• Host: GitHub
• URL: https://github.com/somefive/covid-19-search
• Owner: Somefive
• License: mit
• Created: 2020-05-05T14:42:17.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2023-01-05T20:05:25.000Z (about 2 years ago)
• Last Synced: 2024-11-01T03:23:27.959Z (2 months ago)
• Topics: covid-19, information-retrieval, search-engine
• Language: TypeScript
• Size: 3.22 MB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 24
• Metadata Files:
  • Readme: README.md

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README

        
# [COVID-19 Search](https://somefive.github.io/COVID-19-Search/)

#### Author: Da Yin

This project is a front-end website for a search engine designed for COVID-19 related information. Click [here](https://somefive.github.io/COVID-19-Search/) to visit the website.

![Demo](./docs/Demo.png)

### Main Features

- Instant Search: Any typings will receive response immediately.

- Advance Search: You may customize the search by changing the page size or sorting metric.

- Event exploration: The related events are calculated by k-nearest neighbors on pre-trained graph embeddings.

- Region Search: Searching for locations such as `Beijing` or `China` will get the infection data.

- Entity Search: Searching for entities such as `Coronavirus` will get the entity knowledge.

![Location](./docs/Location.png)

![Entity](./docs/Entity.png)

### Techniques

Front-end website is bootstrapped with [React Create App](https://github.com/facebook/create-react-app) written in mainly Typescript. The search engine is largely implemented with a simple text search on MongoDB. The segmentation on Chinese texts uses [jieba](https://github.com/fxsjy/jieba).

The back-end services is mainly provided by [AMiner COVID-19](https://covid-dashboard.aminer.cn) including the infection data and the news data. The entity search dynamically calls the API from [XLore](https://xlore.org/).

The related events are calculated using k-nearest neighbor based on graph embeddings generated by ProNE [1]. The graph is constructed by connected news and segmented words.

[1] [Zhang, Jie et al. “ProNE: Fast and Scalable Network Representation Learning.” *IJCAI* (2019).](https://github.com/THUDM/ProNE)