We all know, how challenging it is to find the job that meets all your expectations and requirements. LinkedIn is one of the largest job portals which connects job seekers to recruiters throughout the globe. There are innumerable jobs in various industries, but in order to find the job based on an individual's requisites, it obligates the need for one, to make seperate searches. In order to identify and tag the specific requirements for targeted searches, we bring to you Savitar, a Chrome Extension that helps you summarize a linkedin job posting so you dont have to spend your time reading through job descriptions that may not be relevant to you!
- Download the extension using the link provided above.
- Open the extensions tabe in Google Chrome and drag the extension in it to install.
- Clone the github repository.
- Open the extension tab and enable the developer mode using toggle button.
- Click on 'Load Unpacked Extension' and select the root directory of extension.
- clone the github repository.
cd Savitar- Run
npm install - Run
npm run-script buildto package the application
- Run
npm run-script document
- Run
npm test
- Run
npm run-script lint
Savitar is a chrome extension for LinkedIn that is targeted to solve the use case of reducing the time job seekers spend time in reading the job requirements. In particular, it helps us to find important information from job descriptions such as Job Location, Skills Required, Years of Experience and Sponorship. We can easily use this extension to get the important items easily. On an average, people spend one hour daily in simply reading the job descriptions beacuse these critical details are often mixed in a long text or somewhere after a long description on work responsibilities. But if we don't fit in the criteria then the work responsibilities hardly matter to we as we are not elgible for it. The other existing extensions provide summary in the form of text. Our extension provides badges like years of experience, skills, location and sponsorship.
- The project setup is simple and can be done by downloading the .crx file and loading it into chrome as mentioned above.
- The user will be provided with 20 job descriptions and will be asked to identify 5 relevant jobs. The time taken by the user will be recorded.
- Now the user will be asked to perform same task, but by using Savitar and time will be recorded.
- The time difference will serve as a measure to effectiveness of Savitar
- The user will be provided with a list of 20 job descriptions and there will be on job which will be irrelevant.
- The task of the user is to identify this job within given time frame.
- The evaluation will be based on whether the user is able to identify that job within the given time frame.
- The main objective behind this experiment is to identify relevant skills for someone entering the industry.
- The user will be provided with a list of 20 job description and the user has to find top 5 most in-demand skills.
- The evaluation will be done based on whether the user was able to identify relevant skills.
- Completed integrating the Chrome extension with LinkedIn.
- Temporary filters put in place based on candidate requirements which highlight the presence of the required job components.
- Completed integrating features such as "Location", "Years of Experience" by parsing and extracting the fields from job description.
- Integrated the feature of 'Skills' using Named Entity Recognition.
- Represented the new features as badges in the job posting description. .
- Incorporating notification based services for jobs searched by the candidate and setting triggers for job alerts.
- Fulfill all requirements related to deployment of the extension to Chrome store.
- Expanding the scope of the project to other portals such as Indeed, Monster.com etc. for the best possible user experience and time saving.
- Integrate more features such as GPA Required, Eligibility criteria, Personalized job profile etc.