What-To-Taste: A Food Recommendation System
Keywords:
Content Based approach, Information Retrieval, Collaborative Based ApproachAbstract
The Food recommendation system software is relatively new in this era, with the recommendation system that focuses on the user preferences posited. Generally we get confused about what to eat or try next, this problem is solved by our project, which recommends food according to customer’s experience, customer’s ratings on cuisine and customer’s taste.
“What-To-Taste” is a food recommendation system which can be used by the food chain industry to keep recommending their customers about the cuisine, basically whatever they have in their menu, based on their customer tastes, interests and order history. Each human has a different taste that can be verified from recommendation data at every new place and the best cuisine served is location-dependent by rating through the customer.
The Food recommendation system recommends by Food profiling, User profiling, and recommending the specific food item as per the last feedback submitted by the users.
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References
Sibal, Vatika.. Food: Identity of Culture and Religion. July-Aug, 2018 Volume 6, 10908-10915)
D.S.Gaikwad,Anup.V.Deshpande,A Food Recommendation System .IRJET, Maharashtra,2017,p-ISSN: 2395-0072
Content-based filtering algorithm
http://recommender-systems.org/content-based-filterin g/
Faisal Rehman,Osman Khalid(2017),Diet-Right: A Smart Food Recommendation System,DOI: 10.3837/tiis.2017.06.006
Trattner, Christoph & Elsweiler, David. (2017). Food Recommender Systems: Important Contributions, Challenges and Future Research Directions.
Min, W., Jiang, S., & Jain, R. C. (2019). Food Recommendation: Framework, Existing Solutions and Challenges. IEEE Transactions on Multimedia,p-ISSN: 1520-9210, DOI: 10.1109/TMM.2019.2958761
Varga E. Recommender Systems. In: Practical Data Science with Python 3. Apress, Berkeley, CA,2019, pISBN 978-1-4842-4858-4.
https://towardsdatascience.com/introduction-to-recom mender-systems-6c66cf15ada
Carroll County Foods “food chain industry https://industrytoday.com/food-chain
Shuvayan Das (11/08/2015) Beginner Guide to learn Content Based Recommender Engines. Analytics Vidhya.
Thom Hopmans (11/02/2016) A recommendation system for blogs: Content-based similarity (part 2). The Marketing Technologist.
https://www.themarketingtechnologist.co/a-recommen dation-system-for-blogs-content-based-similarity-part 2/
Kunal Deshmukh (16/03/2018) Collaborative Filtering in Recommendation Systems. Medium.com
https://medium.com/kunalrdeshmukh/collaborative-filt ering-in-recommendation-systems-2fa49be8f518
Guillaume Ferry. Python Machine Learning Prediction with a Flask Rest API. Toptal.com.
https://www.toptal.com/python/python-machine-learni ng-flask-example
Breakfast. Better Health Channel.
https://www.betterhealth.vic.gov.au/health/healthylivi ng/breakfast
Recommender System Wikipedia.
https://en.wikipedia.org/wiki/Recommender_system [16]Tavish Srivastava (07/04/2015) Information Retrieval System explained in simple terms. Analytics Vidhya. https://www.analyticsvidhya.com/blog/2015/04/inform ation-retrieval-system-explained/
Faith Gedikli (29/03/2013) ‘Recommendation System and the social web’ Springer
https://books.google.co.in/books?id=YWVEAAAAQB AJ&pg=PA23&lpg=PA23&dq= false
F.O.Isinkaye,Y.O.Folajimi,B.A.Ojokoh,Recommendat ion systems:Principles,methods and evaluation,Egyptian Informatics Journal,2015,pages 261-273
