Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Top Down Approach to find Maximal Frequent Item Sets using Subset
  Creation   Association rule has been an area of active research in the field of
knowledge discovery. Data mining researchers had improved upon the quality of
association rule mining for business development by incorporating influential
factors like value (utility), quantity of items sold (weight) and more for the
mining of association patterns. In this paper, we propose an efficient approach
to find maximal frequent itemset first. Most of the algorithms in literature
used to find minimal frequent item first, then with the help of minimal
frequent itemsets derive the maximal frequent itemsets. These methods consume
more time to find maximal frequent itemsets. To overcome this problem, we
propose a navel approach to find maximal frequent itemset directly using the
concepts of subsets. The proposed method is found to be efficient in finding
maximal frequent itemsets.

11
The categories of this paper are: hep-lat
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics