Chrome extension that determines damping factor to improve Pagerank algorithm

Background

The main goal of this project was to create a Chrome extension that captures users’ browsing actions and uses this information to determine their damping factor. Such a method that accurately determines users’ damping factor can be used to create personalized page ranking algorithms

Implementation

We created a Chrome extension that captures a user’s browsing actions and logs their number of page changes (p) and the number of links they click (l) to calculate their damping factor as l/p. The methodology of our code is as follows. When a user installs the extension, the code initializes storage values for the number of page changes and link clicks. Next, the code adds a listener for page changes using the “onUpdated” Chrome event. The listener is fired whenever the page/tab changes. When the listener is fired, it increments the page changes gathered by one and injects a script into the website to listen for link clicks. Our methodology measures link clicks by taking all clicks on a page and checking if our click’s ”target” has an ”href” attribute, which causes an HTML element to act as a link. After, a JavaScript file reads and displays the two logged values for the damping factor in the options page of the extension.

Languages used: Julia, Javascript