Pre-Process Natural Language - Computer Science Assignment Help

Assignment Task

1. Overview Nowadays there are many job hunting websites including seek.com.au and au.indeed.com. These job hunting sites all manage a job search system, where job hunters could search for relevant jobs based on keywords, salary, and categories. In previous years, the category of an advertised job was often manually entered by the advertiser (e.g., the employer). There were mistakes made for category assignment. As a result, the jobs in the wrong class did not get enough exposure to relevant candidate groups. With advances in text analysis, automated job classification has become feasible; and sensible suggestions for job categories can then be made to potential advertisers. This can help reduce human data entry error, increase the job exposure to relevant candidates, and also improve the user experience of the job hunting site. In order to do so, we need an automated job ads classification system that helps to predict the categories of newly entered job advertisements. This assessment includes two milestones. The first milestone (NLP) concerns the pipeline from basic text preprocessing to building text classification models for predicting the category of a given job advertisement. Then, the second milestone will adopt one of the models that we built in the first milestone, and develop a job hunting website that allows users to browse existing job advertisements, as well as for employers to create new job advertisements. This assessment description is about Milestone

1: Natural Language Processing.

2. Learning Outcomes

This assessment relates to following learning outcomes of the course:

CLO 4: Pre-process natural language text data to generate effective feature representations;

CLO 5: Document and maintain an editable transcript of the data pre-processing pipeline for professional reporting

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