Assume you are working on an online shopping website. For online sales, you have a very long list of items in the list (the number of items are more than a million), there are many products that have redundant information and names under different categories so you want to eliminate them to reduce the item list. For example, there are two different mobile devices information named Apple iPhone 10 and iPhone X but actually, both names refer to the same product and mobile phone so why do we need to store duplicate names to unnecessarily increase the product size. Another example I observe recently different masks names for COVID-19 referring to the same product for example Amazon selling the same product using different names. Suppose your required task is to rename all the redundant names to one common name. However, to perform this task you need to find the products having duplicate names. what type of learning you will use to solve this problem.think about what are the inputs, outputs, etc. Select one: A. unsupervised B. none C. supervised

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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Assume you are working on an online shopping website. For online
sales, you have a very long list of items in the list (the number of
items are more than a million), there are many products that have
redundant information and names under different categories so you
want to eliminate them to reduce the item list. For example, there are
two different mobile devices information named Apple iPhone 10 and
iPhone X but actually, both names refer to the same product and
mobile phone so why do we need to store duplicate names to
unnecessarily increase the product size. Another example I observe
recently different masks names for COVID-19 referring to the same
product for example Amazon selling the same product using different
names. Suppose your required task is to rename all the redundant
names to one common name. However, to perform this task you need
to find the products having duplicate names. what type of learning
you will use to solve this problem..think about what are the inputs,
outputs, etc.
Select one:
O A. unsupervised
B. none
C. supervised
Transcribed Image Text:Assume you are working on an online shopping website. For online sales, you have a very long list of items in the list (the number of items are more than a million), there are many products that have redundant information and names under different categories so you want to eliminate them to reduce the item list. For example, there are two different mobile devices information named Apple iPhone 10 and iPhone X but actually, both names refer to the same product and mobile phone so why do we need to store duplicate names to unnecessarily increase the product size. Another example I observe recently different masks names for COVID-19 referring to the same product for example Amazon selling the same product using different names. Suppose your required task is to rename all the redundant names to one common name. However, to perform this task you need to find the products having duplicate names. what type of learning you will use to solve this problem..think about what are the inputs, outputs, etc. Select one: O A. unsupervised B. none C. supervised
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