Database Question
A certain fastfood chain restaurant is very well known on the country and thereby serves a hundreds of
customers per branch. A certain branch manager has decided to analyze their daily sales transaction in
order to come up with promos or combo of meals that their customers will surely like. To start off, he
tasked experts to perform a data mining technique in order to analyze a certain transaction of a day.
Generating a total of twenty-one (21) sample transactions and using five of their best selling items, they
come up with the following:
• The Transaction_ID began at 1000 and ended at 1020.
• Burger was seen purchased at transactions: 1000, 1003, 1004, 1005, 1014, 1015, 1016 and 1020.
• Fries was purchased at transactions: 1000, 1001, 1003, 1004, 1006, 1007, 1008, 1009, 1011, 1012,
1013, 1014, 1015, 1016, 1017 and 1019.
• Coke was purchased at: 1000, 1002, 1005, 1006, 1009, 1010, 1013, 1014 and 1020.
• Chicken was seen purchased at: 1001, 1002, 1007, 1011, 1012, 1013, 1017 and 1018.
• Extra-Rice was in: 1002, 1007, 1011, 1012, 1013, 1017 and 1018.
3 | P a g e
The restaurant now plans to create a 2 2-item combo meal and 2 3-item combo meal if a certain sales
instance (in percentage) is met:
• Burger-fries combo meal if sales instance is more than 20%
• Chicken with Extra-Rice combo if sales instance is more than 60%
• Burger-fries-Coke if sales instance is more than 20%
• Chicken-Coke-Fries if sales instance is more than 40%
Things to do:
1. Generate a table to plot the transactions and items stated.
2. Identify the total number of transactions made for each items.
3. Perform Apriori Algorithm and use 2-items sets for all possible item combinations.
4. Use 3-itemsets for up to 5 possible combinations.
5. Compute for the frequency rates of all 2-itemsets and the 5 combinations of the 3-itemsets you
have generated.
6. Identify whether or not the combo meals will be possible.
Extracted text: III. Apriori Data Mining Algorithm. A certain fastfood chain restaurant is very well known on the country and thereby serves a hundreds of customers per branch. A certain branch manager has decided to analyze their daily sales transaction in order to come up with promos or combo of meals that their customers will surely like. To start off, he tasked experts to perform a data mining technique in order to analyze a certain transaction of a day. Generating a total of twenty-one (21) sample transactions and using five of their best selling items, they come up with the following: The Transaction_ID began at 1000 and ended at 1020. Burger was seen purchased at transactions: 1000, 1003, 1004, 1005, 1014, 1015, 1016 and 1020. Fries was purchased at transactions: 1000, 1001, 1003, 1004, 1006, 1007, 1008, 1009, 1011, 1012, 1013, 1014, 1015, 1016, 1017 and 1019. Coke was purchased at: 1000, 1002, 1005, 1006, 1009, 1010, 1013, 1014 and 1020. Chicken was seen purchased at: 1001, 1002, 1007, 1011, 1012, 1013, 1017 and 1018. Extra-Rice was in: 1002, 1007, 1011, 1012, 1013, 1017 and 1018.
Extracted text: The restaurant now plans to create a 2 2-item combo meal and 2 3-item combo meal if a certain sales instance (in percentage) is met: Burger-fries combo meal if sales instance is more than 20% Chicken with Extra-Rice combo if sales instance is more than 60% Burger-fries-Coke if sales instance is more than 20% Chicken-Coke-Fries if sales instance is more than 40% Things to do: 1. Generate a table to plot the transactions and items stated. 2. Identify the total number of transactions made for each items. 3. Perform Apriori Algorithm and use 2-items sets for all possible item combinations. 4. Use 3-itemsets for up to 5 possible combinations. 5. Compute for the frequency rates of all 2-itemsets and the 5 combinations of the 3-itemsets you have generated. 6. Identify whether or not the combo meals will be possible.