please i want to know the list of efficient and fast maximal frequents itemset extraction algorithm.
i find GenMax as an efficient one,is it the only one.
another question, i read some paper where the authors developpe (make the source code of some data mining algorithm "FP max as an example " and they publish a paper
But maybe that I have missed some. I did not do an extensive search on this topic. You can may be find more on Google Scholar.
For the second question, implementing an existing algorithm is generally not enough to publish a paper unless you improve with some new significant optimizations or data structures and show that it performs better in some conditions. Another possibility is to modify the algorithm so that it does something slightly different. For example, FPMAX is an algorithm for mining maximal itemset. Could we modify it to mine a slightly different kind of itemsets such as maximal fuzzy itemsets? maximal uncertain itemset? etc. That could be interesting. What I mean is that you need to improve the algorithm or show that you add something new.
Hope this helps,
By the way, thank you for updating the conference list!
Thanks for the list of algorithms, for the paper i was speaking about as an example this paper http://dl.acm.org/citation.cfm?id=1802277
Sir could you please tell me where can i find a java source code of any of these algorithm (if there is). I see that you have developped CHARM-MFI but as you said it isn't an efficient one.
I have spent 20 minutes searching on Google but cannot find it.
Here is two ideas: - You could contact the authors of the paper about the Java implementation to ask them if they can send you the code. - Alternatively, I have found this website that seems to have the code: http://en.pudn.com/downloads432/sourcecode/java/detail1827711_en.html But to get the code they ask either to (1) upload five files or (2) to pay.
Otherwise, another solution is to implement it by yourself. But it may be difficult.
It offers an implementation of LCM but I think that it only discovers closed itemsets. I think that the author did not implement the part about maximal itemsets in LCM. I have not tested it. But maybe that it would be possible to modify it to find maximal itemsets. I don't know.
I have make a quick test to see how good this LCM implementation is and it does not seems very fast. I have compared LCM and my implementation of CHARM and DCI-Closed for mining closed itemsets on the Chess dataset with minsup = 85 % and my implementations of CHARM and DCI_Closed finish in less than 1 second, while the LCM code takes about 10 seconds... Moreover, the LCM code does not generate the same amount of results (i don't know why : bug? maximal itemsets? i don't know)
C:\Users\ph\Desktop\SPMF>java -jar spmf.jar run Charm_bitset chess.txt test.txt 85% ============= CHARM - STATS ============= Transactions count from database : 3196 Frequent closed itemsets count : 1885 Total time ~ 800 ms ===================================================
C:\Users\ph\Desktop\SPMF>java -jar lcm-java.jar chess.txt 85 ===================================== Total count: 1672 =====================================