Explain frequent itemset mining.

Frequent itemset mining :-

1. Frequent itemset mining leads to the discovery of associations and correlations among items in large transactional or relational datasets.

2. With massive amounts of data continuously being collected and stored, many industries are becoming interested in mining such patterns from their databases.

3. The discovery of interesting correlation relationships among huge amounts of business transaction records can help in many business decision-making processes such as catalogue design, cross-marketing, and customer shopping behaviour analysis.

4. A typical example of frequent itemset mining is market basket analysis.

5. This process analyzes customer buying habits by finding associations between the different items that customers place in their “shopping baskets”.

6. The discovery of these associations can help retailers to develop marketing strategies by gaining insight into which items are frequently purchased together by customers.

7. For instance, if customers are buying some product, how likely are they to also other products at the same time. This information can lead to increased sales by helping retailers do selective marketing.