• Login
    • Library Home
    View Item 
    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    An empirical study of collaborative filtering algorithms for building a diet recommendation system

    Thumbnail
    View/Open
    13201080, 14101252, 14101003_CSE.pdf (1.556Mb)
    Date
    12/26/2017
    Publisher
    BRAC University
    Author
    Ornab, Ashique Mohaimin
    Chowdhury, Sakia
    Toa, Seevieta Biswas
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/10361/9535
    Abstract
    The purpose of this research is to study the different techniques that can be approached in order to build a recommendation system. Here, we have analyzed the different approaches between two different collaborative filtering algorithms in perspective of a food diet recommendation system. A food recommendation system that will help people to choose their daily meal just the way we select movies to watch from suggestions in Netflix or add a friend in Facebook when the suggestion pops up in our home page. Sometimes people get bored of having the same food items on regular basis hence in order to help them get rid out of this monotonous lifestyle, we have proposed a diet recommendation system. In this paper, we first give you some basic information about what recommendation system is, and then we talk about the two collaborative algorithms and finally tell you what kind of approaches we have used to build a diet recommendation system.
    Keywords
    Cosine similarities; Matrix factorization; ALS; Recommendation system
     
    Description
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (pages 60-61).
     
    This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
    Department
    Department of Computer Science and Engineering, BRAC University
    Type
    Thesis
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering) [1600]

    Copyright © 2008-2024 Ayesha Abed Library, Brac University 
    Contact Us | Send Feedback
     

     

    Policy Guidelines

    • BracU Policy
    • Publisher Policy

    Browse

    All of BracU Institutional RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Copyright © 2008-2024 Ayesha Abed Library, Brac University 
    Contact Us | Send Feedback