Abstract:
Data analysis is a process which is required to analyze a given set of data. This
process is very much needed today where information is extracted and transformed
into a format which is easy to process and interpret. In this paper, we consider
techniques for identifying and classifying ingredients and aim to explore what are
the essential ingredients that are required for a given cuisine. Each nation has its
own unique ingredients that make their cuisine iconic. If we look at a particular
cuisine, estimating its ingredients even if there is sufficient data, is a tedious task as
the ingredients of the same cuisine differ from region to region and according to the
culture. The problems faced by the users in the existing search system is getting just
the recipe and ingredients. It does not classify the essential ingredients required to
cook a particular dish. So, we propose a project that will extract the ingredients of the
given cuisine from various websites on the web with the help of web scraping tools
or techniques, then display the most essential ingredients amongst them by using
data mining techniques and sorting as well as filtering algorithms. Web scraping is a
process of extracting data from the web world through various methods. It involves
fetching a web page and extracting data from it.
Data mining techniques will help predict knowledge-driven decisions. This will
include performing analyses on different data sets extracted and the genuine ingredients
of every individual country, identifying them and then display them after filtration.
Thousands of recipes which represent different national cuisines will be
analyzed so that a better output can be generated which distinguishes the common
and distinctive ingredients of each nation. Only those ingredients will be displayed
which are distinct and do not belong to the users location.
