| Nojaded App: Paper Printing and Recycling Mobile App using Recommender System. |
| Paper ID : 1012-IUGRC5-FULL (R1) |
| Authors: |
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Ramy Ahmed Gomaa *1, Ahmed Magdi Zahran1, Noha hamdy Taha2, Noran Mostafa Abdo2, Mostafa Ahmed Mostafa2, Mostafa Aymen Hassan2 1Cs, Computer Science, Arab Academy for Science Technology & Maritime Transport , Aswan, Egypt 2CS, Computer Science, Arab Academy for Science Technology & Maritime Transport, Aswan, Egypt |
| Abstract: |
| Abstract- Paper Recycling has always been a major issue and according to the Food and Agricultural Organization of the United Nations (FAO), the total global paper use is still steadily increasing. We argue that, among many factors, Homeowners' failure to divide up waste is one of the causes. The objective of this research is to design a mobile application that uses recommendation techniques to ease the paper recycling operations by facilitating communication between the recycling organizations and the paper donors and also facilitating the paper printing operations for users by creating a platform for which they can easily use to print or purchase papers and receive them from their house step. The recommendation engine in this research uses a combination of Collaborative Filtering and Content-based filtering. Collaborative filtering is used to perform data filtering based on the similarities of user characteristic, which will help us identify patterns that choose the appropriate parameters dealing with users, whether it is for paper donation or paper purchasing. Content-based filtering is used to enhance the personalization experience of the user in the paper printing side of the app. The used datasets have features that benefit the recommender system and help build a model for the user. These features are obtained from the printing centers and the users. Each operation has a rating. The filtering methods are measured for accuracy using Mean Absolute Error (MAE). MAE outlines the difference between the original and predicted ratings obtained by averaging the absolute difference over the intended data. |
| Keywords: |
| Recommender System, Content-based Filtering, Collaborative Filtering, Hybrid Filtering, Paper Recycling, Paper Printing, Mobile Application, |
| Status : Paper Accepted (Oral Presentation) |
