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COSC2820 Advanced Programming for Data Science

COSC 2820/2815

Assignment 2: NLP Web-based Data Application

Milestone II: Web-based Data Application

1. Overview

This assessment description concerns Milestone II of the NLP web-based data application project.                     In Milestone I, we have built several machine learning models based on different feature representations of documents to classify job advertisement categories. In Milestone II, we will develop a job hunting website based on the Python Flask web development framework. The developed website will allow job hunters to browse existing job advertisements, as well as employers to create new job advertisements. The website will adopt one of the machine learning models that we built in Milestone I, for the purpose of auto classifying categories for new job advertisement entries. Such functionality helps to reduce human data entry error, increase the job exposure to relevant candidates, and also improve the user experience of the job hunting site.

2. Learning Outcomes

This assessment relates to following learning outcomes of the course:

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

professional reporting;

.   CLO 6: Build small to medium scale data-driven applications using a Web development framework.

3. Assessment details

In this milestone, you are required to build a job hunting website using Python Flask.

Job Data

To test and demonstrate the functionality of job displaying, you will need some job data. In this milestone, you can use data, including the job information and descriptions, given in Milestone I. If you want, you can also create any additional artificial data (e.g. images) for the purpose of display.

Website Layout and Design

The layout and design of the website are flexible. You can refer to the exercises in the last two weeks'             material, or the Job Browsing Page and the Employer site of the commonly used Seek.com.au as a reference. Note that the Employer site would require an seek account login to enter.

Minimum Functional Requirements

There  are  minimum  functional  requirements  of the  developed  website for job  hunters  and  employers, respectively. You feel free to include other functionalities that suit.

Functionality for Job hunters

[Fun 1] Job Display

The Job hunting website will allow job hunters to see all the available job advertisements. In the homepage, the develop website should provide a list view of the available job advertisement previews, and when the users click on the previews, they will be able to see the full description of the job advertisement. The job hunting website will also display job advertisements per category. When users click on each category, they will be able to see a list view of the available job advertisement previews within this category, and when users click on the previews, they will be able to see the full description of the job advertisement.

Functionality for Employers

[Fun 2] Create a New Job Listing

The  Job  hunting  website  will  allow  employers  to  create  a  new  job  listing,  including  entering  various information, e.g., title, description, salary, etc.

Based on the entered title and description, the website should automatically recommend categories of the entered   job   advertisement.   It   should   also   allow   the   employer   to   select   other   categories   if  the recommendation does not suit (i.e. they can overwrite the category suggested by the website). You can refer to the  employer  site  of  seek.com.au  as  an  example.  Upon  confirmation, the  created job advertisement should be included in the job data, and can be found via a URL or relevant search.

Note that you  have the flexibility to choose the language model and the classification model for the job category recommendation task.

For the sake of simplicity, we do not need to create any employer login or verification functionalities.

Record Demo Videos

As part of the final submission, you are required to submit a pre-recorded 5-min video, demonstrating the working system for various functionalities.

6. Marking Guidelines

Marking Criteria

Marking of this milestone will consider the design & layout and the implementation of the website.

Mark Allocations

    Design & Layout [1%]

    Implementation of functional requirements [6%]

o     [Fun 1] Job Browsing (3%)

o     [Fun 3] Create a New Job Listing (3%)

●    Demo Video [3%]

4. Submission

The final submission of this milestone will consist of:

●   The python source code of the developed website, as well as files/data that are required to locally host the website.

○    Note, the assessor will re-run your code. Please make sure all necessary files to run your code  are  included  in your  submission.  If some files are too large, you can put them in a OneDrive link, and put the link in a README.txt file to be included in the submission.

   All source code will be passed to a plagiarism checker to ensure academic integrity.

●   A pre-recorded 5-min demo video. If your video is too large to upload to canvas, you can also put it in OneDrive and share the link along with your submission.

●    Put all the above mentioned files in a folder, named with your student id, Zip the folder with the same name (i.e., <student_number>.zip) and upload for submission

Assessment declaration:

When you submit work electronically, you agree to the assessment declaration:

https://www.rmit.edu.au/students/student-essentials/assessment-and-exams/assessment/assessment-decla ration

Late  Submission  Penalty

Late  submissions  will  incur  a  10%  penalty  on  the  total marks  of  the  corresponding  assessment  task per   day  or  part  of  day  late.    Submissions that are late by 5 days or more are not accepted and will be awarded zero, unless special consideration has been granted.   Granted Special Considerations with a new due  date  set  more  than  2  weeks  after  the  original  due  will  automatically    result    in    an    equivalent assessment  in  the  form  of  a  practical  test with interview,  assessing  the same knowledge and skills of the assignment (location and time to be arranged by the instructor).  Please ensure your submission is correct (all files  are  there,    compiles  etc),  re-submissions  after  the  due  date  and time  will  be  considered  as  late submissions.

5. Academic integrity and plagiarism (standard warning)

Academic integrity is about honest presentation of your academic work. It means acknowledging the work of others  while  developing your own insights, knowledge and ideas. You should take extreme care that you have:

●   acknowledged words, data, diagrams, models, frameworks and/or ideas of others you have quoted (i.e. directly copied), summarised, paraphrased, discussed or mentioned in your assessment through the appropriate referencing methods,

●   provided a reference list of the publication details so your reader can locate the source if necessary. This includes material taken from Internet sites.

If you do not acknowledge the sources of your material, you may be accused of plagiarism because you have passed off the work and ideas of another person without appropriate referencing, as if they were your own.

RMIT  University treats  plagiarism  as  a very serious offence constituting misconduct.   Plagiarism covers a variety of inappropriate behaviours, including:

    Failure to properly document a source

    Copyright material from the internet or databases

●    Collusion between students

For        further        information        on        our        policies        and        procedures,        please        refer        to

https://www.rmit.edu.au/students/student-essentials/rights-and-responsibilities/academic-integrity