Implementing a recommender system for Bangladeshi faculty search using machine learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

מידע ביבליוגרפי
מחבר ראשי: Hasan, Md.Khalid
מחברים אחרים: Arif, Hossain
פורמט: Thesis
שפה:en_US
יצא לאור: Brac University 2020
נושאים:
גישה מקוונת:http://hdl.handle.net/10361/14061
id 10361-14061
record_format dspace
spelling 10361-140612022-01-26T10:19:58Z Implementing a recommender system for Bangladeshi faculty search using machine learning Hasan, Md.Khalid Arif, Hossain Department of Computer Science and Engineering, Brac University Recommender System Faculty Search Machine Learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 22-24). Machine learning is a one of the popular fields in Computer Science. In my thesis research the focus is to implement a recommender system for Bangladeshi faculty search. Selecting a appropriate faculty or thesis supervisor is a very important part in a student’s life. Even choosing right academy is also an important part in their study life. This research paper presents a faculty recommender system to assist students in making these choices. Here the main focus is to cover our own country, Bangladesh, to help the students of our country to pursue their own interest. I proposed this recommender system by using collaborative filtering algorithm. I used a very popular machine learning algorithm, K-Nearest Neighbor algorithm with cosine similarity to predict faculty members. It works on a vast database and being analyzed by different criteria. It applies multiple filtering conditions to retrieve relevant supervisor or faculty member based on the research interest or preferences. The preference field of the faculties based on preferred research area, making part of the decision specific. This system helps a user finding faculty or supervisor according to own individual interests. It contains information about faculties around Bangladesh from different institutions. A classification accuracy of 76.0 % for the predicted results ac hived by the proposed model. Md.Khalid Hasan B. Computer Science 2020-10-18T06:04:42Z 2020-10-18T06:04:42Z 2019 2019-12 Thesis ID: 12101102 http://hdl.handle.net/10361/14061 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 24 pages application/pdf Brac University
institution Brac University
collection Institutional Repository
language en_US
topic Recommender System
Faculty Search
Machine Learning
spellingShingle Recommender System
Faculty Search
Machine Learning
Hasan, Md.Khalid
Implementing a recommender system for Bangladeshi faculty search using machine learning
description This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.
author2 Arif, Hossain
author_facet Arif, Hossain
Hasan, Md.Khalid
format Thesis
author Hasan, Md.Khalid
author_sort Hasan, Md.Khalid
title Implementing a recommender system for Bangladeshi faculty search using machine learning
title_short Implementing a recommender system for Bangladeshi faculty search using machine learning
title_full Implementing a recommender system for Bangladeshi faculty search using machine learning
title_fullStr Implementing a recommender system for Bangladeshi faculty search using machine learning
title_full_unstemmed Implementing a recommender system for Bangladeshi faculty search using machine learning
title_sort implementing a recommender system for bangladeshi faculty search using machine learning
publisher Brac University
publishDate 2020
url http://hdl.handle.net/10361/14061
work_keys_str_mv AT hasanmdkhalid implementingarecommendersystemforbangladeshifacultysearchusingmachinelearning
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