ECLAT Algorithm to find maximal and closed frequent sets

Question

Transaction ID  Items
     1        {A, C, D}
     2        {B, C, E}
     3        {A, B, C, E}
     4        {B, E}
     5        {A, B, C, E}
Minimum support count is 3. Determine maximal frequent and closed frequent itemset using ECLAT Algorithm.

Can someone please explain how to get maximal frequent and closed frequent itemset? I have been trying to find sources online and havent been able to find satisfactory explanations to solve this. At max, I have been able to solve till a final table of supports but beyond that, haven't been able to find a way to find the required sets.

Answer 1

Creating Support Tables:
Minsup>=3
For k=1, 
Sr. No  Itemset Support
1        {A}    3
2        {B}    4
3        {C}    4
4        {D}    1
5        {E}    4
For k=2,
6   {A, B}  2
7   {A, C}  3
8   {A, E}  2
9   {B, C}  3
10  {B, E}  4
11  {C, E}  3
For k=3,
12  {A, B, C}   2
13  {A, B, E}   2
14  {A, C, E}   2
15  {B, C, E}   3
For k=4,
16  {A, B, C, E}    1
Since Minsup>=3,
We eliminate Itemsets 4, 6, 8, 12, 13, 14, 16 as their support is <3.
Hence,
Maximal Frequent Itemset: {B, C, E}
Closed Frequent Itemset: {A, C} & {B, C, E}