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webmasterphilfv
Those are mostly the same thing. In simple words, two graphs are isomorphic if we map the edges and vertices of one graph to the other and they are equivalent. Subgraph isomorphim checking is the same thing. But since you add the word "subgraph" it means that you are comparing subgraphs of a graph to check if these subgraphs are equivalent. Yes, the idea of graph isomorphism is
Forum: The Data Mining / Big Data Forum
2 days ago
webmasterphilfv
Hello, Yes, I call this a class sequential rules. There is this algorithm in SPMF: the TopSeqClassRules algorithm for mining the top-k class sequential rules that does that. It will let you select {i} to find the k most frequent sequential rules of the form X --> {i}. This algorithm is similar to RuleGrowth but modified to do that. Best Philippe
Forum: The Data Mining / Big Data Forum
3 days ago
webmasterphilfv
Hello, Sorry for the delay to answer. I saw your e-mail but actually was too busy in the last few days. I will provide some answer/opinion/suggestion below. How to represent the data is always a good question because depending on how you represent the data, you may obtain different results using a data mining algorithms. A possibility could be that each sequence represents a sequence o
Forum: The Data Mining / Big Data Forum
3 days ago
webmasterphilfv
Hi Victor, I see. There is no such implementation in SPMF that does exactly that. It could be done, I think, but it would require some programming to modify the algorithm and it can be more or less complicated. If one modifies it, then it would need to check to make sure that the algorithm remains correct, and sometimes combining two ideas results in an algorithm that cannot find all the patter
Forum: The Data Mining / Big Data Forum
6 days ago
webmasterphilfv
Hi, 1) the likely reason is that the input format is not correct. At the end of each itemset, there should be a -1 to separate. For example, the first sequence should be in this format: <10> 42 45 -1 <11> 31 42 45 -1 <20> 18 23 31 42 45 -1 <36> 48 -1 -2 It is the same for the other sequences. 2) Yes, if you have a pattern: <0> 1 2 <1> 3
Forum: The Data Mining / Big Data Forum
6 days ago
webmasterphilfv
Great. I will fix the error in the documentation. Thanks for reporting it.
Forum: The Data Mining / Big Data Forum
7 days ago
webmasterphilfv
Hi Victor, I will answer your question below. > So how large this large should be set to make it > exact not approximate algorithm? Does it depends > on data size? The problem with the maximal time interval constraint is that if you apply this constraint when doing closed sequential pattern mining, you may miss some patterns. If you don't care about missing a few patterns
Forum: The Data Mining / Big Data Forum
9 days ago
webmasterphilfv
Dear Victor, > My current way of defining itemset is that for a > sequence of events that a customer took in the > history, an itemset is the events happened in the > same day. So in the final frequent sequence, I am > able to know this sequence covers how many days. > But I also want to reserve the original order of > events in an itemset. So what if I reserve the &
Forum: The Data Mining / Big Data Forum
11 days ago
webmasterphilfv
Dear Victor, I have now added the feature. It is available in the new version of SPMF (2.33) Best regards, Philippe
Forum: The Data Mining / Big Data Forum
12 days ago
webmasterphilfv
Hello all, This is to let you know that we are looking for paper for the third and fourth issues of the DSPR journal (Data Science and Pattern Recognition). See the website below for information: http://dspr.ikelab.net/ Best regards, Philippe
Forum: The Data Mining / Big Data Forum
14 days ago
webmasterphilfv
Dear Sandra, Very happy to hear that it works well. :-) Best regards,
Forum: The Data Mining / Big Data Forum
14 days ago
webmasterphilfv
Hi Victor, Yes, in sequential pattern mining the order in itemsets should not be important. However, for practical purposes, all itemsets should be sorted according to some order in your input file, as explained in the documentation: QuoteNote that it is assumed that items are sorted according to a total order in each itemset and that no item appears twice in the same itemset. That orde
Forum: The Data Mining / Big Data Forum
16 days ago
webmasterphilfv
Hello, Yes, there exists a few algorithms for mining closed sequential patterns with gap constraints. In SPMF, you would need to use the Fournier08-closed+time algorithm to get that. That algorithms actually is designed to work with timestamps but if you set all the timestamps to 0, it should do what you want. This is the example from the documentation: http://www.philippe-fournier-viger.
Forum: The Data Mining / Big Data Forum
17 days ago
webmasterphilfv
In theory, results should be the same. What parameters have you used? What dataset? If you send me the data, I can check it. My e-mail is philfv8 AT yahoo.com By the way, note that if the input format is incorrect, it is possible that the algorithms would not generate the correct result because of this.
Forum: The Data Mining / Big Data Forum
17 days ago
webmasterphilfv
Hi Victor, I think that it can be possible. I will check how to do it tomorrow. I am currently attending PAKDD 2018. But I should have a bit of time tomorrow to see if i can implement that feature easily ;-) Best, Philippe
Forum: The Data Mining / Big Data Forum
23 days ago
webmasterphilfv
Hello all, A new survey on parallel sequential mining has been published on Arxiv by my collaborators and me: Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Tseng, V. S., Yu, P.. A Survey of Parallel Sequential Pattern Mining. https://arxiv.org/pdf/1805.10515.pdf Best,
Forum: The Data Mining / Big Data Forum
23 days ago
webmasterphilfv
Hello all, A new survey on high utility pattern mining has been published on Arxiv by my collaborators and me: Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Tseng, V. S., Yu, P.. A Survey of Utility-Oriented Pattern Mining. https://arxiv.org/pdf/1805.10511.pdf If you want to know more about high utility pattern mining, you can read it. It is quite comprehensive as it surveys mo
Forum: The Data Mining / Big Data Forum
23 days ago
webmasterphilfv
Dear Dang, It is great that you share this! I think it will be useful to many. Thanks, Philippe
Forum: The Data Mining / Big Data Forum
25 days ago
webmasterphilfv
Dear Andrea, Yes, there is some Java code for that. But it is a student project and it is not public because I did not have time to clean the code and package it properly. And since then, I have included other algorithms for sequence predictions in SPMF. But if you are interested to get that code, I can send it to you by e-mail. Although the code may not be so clean, I think it should not be
Forum: The Data Mining / Big Data Forum
30 days ago
webmasterphilfv
Call for Papers 2018 IEEE International Conference on Big Data (IEEE Big Data 2018) http://cci.drexel.edu/bigdata/bigdata2018/index.html December 10-13, 2018, Seattle, WA, USA In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data confer
Forum: The Data Mining / Big Data Forum
4 weeks ago
webmasterphilfv
I guess you mean "pseudocode". Yes, in that paper, the description of the algorithm is not very clear. Actually, the authors of the paper kind of assume that you are already familiar with Apriori because Two-phase is based on Apriori. You can always check the SPMF source code of Two-Phase in Java to understand the algorithm and then try to implement it in C#. Best,
Forum: The Data Mining / Big Data Forum
5 weeks ago
webmasterphilfv
Hi Andrea, You can definitely try these algorithms (RuleGrowth / ERMiner) to discover sequential rules, which could be use to suggest activities to learners. You could consider using the TRuleGrowth algorithm for example, which is an improved version of RuleGrowth offering and additional window parameter. As for using SPMF from Python, a very simple way could be to call the spmf.jar as an
Forum: The Data Mining / Big Data Forum
5 weeks ago
webmasterphilfv
Thanks for your feedback :-)
Forum: The Data Mining / Big Data Forum
5 weeks ago
webmasterphilfv
Hello, Sorry i dont have this. Best regards,
Forum: The Data Mining / Big Data Forum
6 weeks ago
webmasterphilfv
The deadline has been extended to the 21st May!
Forum: The Data Mining / Big Data Forum
6 weeks ago
webmasterphilfv
I am not much familiar with deep learning. I know about neural works but did not study much the novelty in the deep neural networks. But for neural networks in general, yes, you can use genetic or evolutionary algorithms to evolved some neural networks, so think it is certainly doable for deep learning. Someone has actually certainly tried this already so perhaps that you should do some search to
Forum: The Data Mining / Big Data Forum
6 weeks ago
webmasterphilfv
IOT is very interesting topic for data science and data mining. I think that what you want to do is a literature review. Then, I recommend to search with a search engine to find the recent papers in top conferences and journal related to your topic. You can use Google Scholar for example and search by years to find good and recent papers. Hope this helps
Forum: The Data Mining / Big Data Forum
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