https://github.com/rashikakarki/related-articles-wikipedia

Using Wikipedia Clickstream data to find related articles to the searched term..
https://github.com/rashikakarki/related-articles-wikipedia

Last synced: 15 days ago
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Using Wikipedia Clickstream data to find related articles to the searched term..

• Host: GitHub
• URL: https://github.com/rashikakarki/related-articles-wikipedia
• Owner: RashikaKarki
• Created: 2021-04-30T08:48:22.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2022-10-10T14:57:50.000Z (about 2 years ago)
• Last Synced: 2024-10-18T17:49:41.969Z (19 days ago)
• Language: Python
• Size: 1.67 MB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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README

        
# Related Articles Wikipedia

![Demo](https://github.com/RashikaKarki/Related-Articles-Wikipedia/blob/main/resource/demo.gif)

A simple web application that gives you list of related articles to the searched term in wikipedia. Uses Wikipedia Clickstream data.

## About the data:

> The data contains counts of (referer, resource) or (source, destination) pairs extracted from the request logs of Wikipedia.

### Format of the data

The data has 4 columns: Source, Destination, Type and TotalNum

- **Source :** The result of mapping the source/referrer URL to the fixed set of values

  - **the article title** : an article in the main namespace

  - **other-internal** : a page from any other Wikimedia project

  - **other-search** : an external search engine

  - **other-external** : any other external site

  - **other-empty** : an empty source

  - **other-other** : anything else

- **Destination :** The title of the article client requested

- **Type :** Described the relation between source and destination

  - **link** : if the source and request are both articles and the source links to the request

  - **external** : if the source host is not en(.m)?.wikipedia.org

  - **other** : if the source and request are both articles but the source does not link to the request. This can happen when clients search or spoof their refer.

- **TotalNum :** The number of occurrences of the (source, destination) pair

The data can be found at: https://dumps.wikimedia.org/other/clickstream/

## How to run the application locally?

- Step 1:

  Clone the repo

- Step 2:

  Install the required packages:

  `pip install -r requirements.txt`

- Step 4:

  Rename the `.env.example` file to `.env`

- Step 3:

  Run the application

  ```

  flask run

  ```

The server will run on port `5000`