SYSTEM FOR TURKISH CUISINE Supervisor Assist. Prof. Dr. Engin DEMR - - PowerPoint PPT Presentation

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SYSTEM FOR TURKISH CUISINE Supervisor Assist. Prof. Dr. Engin DEMR - - PowerPoint PPT Presentation

Jan 11, 2024 463 likes •810 views

RECIPE RECOMMENDATION SYSTEM FOR TURKISH CUISINE Supervisor Assist. Prof. Dr. Engin DEMR Prepared by 201112031 Damla Pnar GVENER 201211001 Esin AIK 201211042 Hivda ZATLI 2 Contents Definition of the Problem Literature Review

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RECIPE RECOMMENDATION SYSTEM FOR TURKISH CUISINE

Supervisor

  • Assist. Prof. Dr. Engin DEMİR

Prepared by

201112031 Damla Pınar GÜVENER 201211001 Esin AÇIK 201211042 Hivda ÖZATLI

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Contents

Definition of the Problem Literature Review Software Requirement Analysis Software Design Future Plan Conclusion References

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What is the Recommendation System?

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Can we call for recommendation?

 yes  to know what we are looking for

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Definition of the Problem

 hardness of making decision between lots of food recipes  health (calories), time constraints  hardness of food selection in group organization  hardness of food selection for people who allergic to smth.

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Definition of the Problem

Motivation

 beneficial for Turkish people  to generate accurate recommendation for all types of user  to provide making weekly meal plan

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Literature Review

 Recommendation System  Challenges of this Project

  • cold-start problem
  • changing preferences

 Recommendation Techniques  Algorithms  User’ Rating

User/Recipe R1 R2 R3 R4 U1 4 5 2 U2 3 1 U3 2 2 5 7

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Literature Review

Recommendation Techniques

 Collaborative Filtering

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Literature Review

Recommendation Techniques

 Content-Based Filtering

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Literature Review

Recommendation Techniques

 Hybrid Filtering

Input Input CF Based Recommender Content Based Recommender Combiner Recommendation

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Literature Review

Algorithms

Memory-Based Algorithm  Model-Based Algorithm

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Literature Review

Existing Recommendation Systems

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Literature Review

Our Differences

 A New System for Turkish Cuisine  Document Database

  • fast search, flexible in terms of relationship

 Comprehensive System

  • calories, nutrition, allergies, diets, cost, time

likes/dislikes

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Software Requirement Analysis

Functional Requirement Specifications

 User Use-Case  Admin Use-Case  System Use-Case (Recommendation Engine)

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Non-functional Requirements

 accessability  usability  performance  security

Software Requirement Analysis

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Flow Description

 need about 1000 recipes  user registers then log in to the system  RE recommends 5 different types of recipes  user selects recommended recipe or search a recipe  user rates selected recipe

Software Requirement Analysis

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Waterfall Development Methodology  Scrum Development Methodology  Deployment Diagram  Whole System Sequence Diagram  Interface Design

Software Design

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Waterfall Development Methodology

Software Design

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Scrum Development Methodology

 fast and motivational  efficient work in a short time

Software Design

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Deployment Diagram

Software Design

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Whole System Sequence Diagram

Software Design

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Interface Design

Home Page

Software Design

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Interface Design

Personal Information Page

Software Design

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Interface Design

Preferences Page

Software Design

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Interface Design

Search Page

Software Design

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Interface Design

Recommendation Page

Software Design

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Interface Design

Recipe Page

Software Design

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Interface Design

Recipe Page

Software Design

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Future Plan

 MongoDB (Document database)  VPN (Web Service)  Hybrid Filtering  WEKA (Machine Learning Algorithm)  Data gathering from http://www.nefisyemektarifleri.com https://www.lezzet.com.tr etc.

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Conclusion

What We Have Done Until Now?

Problem Definition and Project Plan Literature Review

  • on Recommender System
  • on Machine Learning and Data Source

Requirement Analysis for System Design Design of System

  • Deployment Diagram
  • Sequence Diagram
  • Interface Design

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References

 J. Leskovec, A. Rajaraman and J. D. Ullman, "Ch 9 - Recommendation Systems," in Mining of Massive Datasets, 2014, pp. 307-343.  By Michael D. Ekstrand, John T. Riedl and Joseph A. Konstan, "Collaborative Filtering Recommender Systems," 2011.  D. Bianchini, V. D. Antonellis, N. D. Franceschi and M. Melchiori, "PREFer: a Prescription-based Food recommender," Computer Standards & Interfaces, 2016.  longqi Yang; Cheng-Kang Hsieh; Serge Belongie; Nicola Dell; Hongjian Yang; Deborah Estrin, "Yum-me: Personalized Healthy Meal Recommender System," 2016.  M. N. Moreno, S. Segrera, V. López, M. D. Muñoz and Á. L. Sánchez, "Web mining based framework for solving usual problems in recommender

  • systems. A case study for movies' recommendation," Neurocomputing-

Elseiver, pp. 72-80, 2016.

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an any qu ques esti tions

  • ns

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