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Shiftati: A mobile app for shift and
temporary workers
Tasneem Ajaj
Marah Salameh
Iman Nassar
Supervised by:Dr. Abdel Salam Sayyad
Introduction
Introduction
Shiftati is a mobile application that will form a special environment for workplaces that are interested in part-time workers, and for workers who are looking for part-time jobs.
Motivation
Motivation
- Part Time workers are constantly shifting jobs.
- Seeking part-time jobs became high in demand.
- No similar applications exist in Palestine that focuses on part-time jobs.
Problem Statement
- Workplaces struggle in searching for reliable workers.
- Workers struggle in looking for good workplaces.
- Workers and workplaces strive to find a solution with minimum cost and effort.
Problem Statement
Related Work
Survey
The first step taken before designing and extracting the features of our application is collecting useful information from various resources.
Apps and
Websites
Related Work
Feature Matrix
Survey
Apps and Websites
Applications
Websites
Feature Matrix
System Design
Tools and Technologies
App development consists of three stages:
- Front-end development stage that focuses on the user interface.
- Back-end server stage that is required for user authentication-authorization date services, and reusable business logic.
- Database stage that is used to organize the data.
System Design
Tools and Technologies
Web application development is built on top of many technologies, the combination of these
technologies is referred to as a stack.
System Implementation
System Implementation
Database
Database
Worker
Workplace
User
Advertisement
Frontend and Backend
Frontend
and Backend
Recommender System
OverView
Recommender system is an information filtering system that seeks to predict ratings that can be given by a user to specific items, when the item’s predicted rate is high, this item will be recommended for user
Recommender System
OverView
User 1
User 2
User 3
Shiftati Recommender System
Shiftati Recommender System
Workers are recommended :
- New advertisements using item and user collaborative based filtering algorithms.
- New workplaces using item collaborative based filtering algorithm.
- New workers to follow using user collaborative based filtering algorithm.
Time is an important factor to increase the accuracy of the recommender system.
Conclusion
Conclusion
Timeline
Timeline
Questions ?