scholarly journals Mining negative sequential patterns from infrequent positive sequences with 2-level multiple minimum supports

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1875-1885
Author(s):  
Ping Qiu ◽  
Long Zhao ◽  
Weiyang Chen ◽  
Tiantian Xu ◽  
Xiangjun Dong
Keyword(s):  
Association Rules ◽  
Negative Association ◽  
Sequential Patterns ◽  
Minimum Support ◽  
Negative Association Rules ◽  
Multiple Minimum Supports

Negative sequential patterns (NSP) referring to both occurring items (positive items) and nonoccurring items (negative items) play a very important role in many real applications. Very few methods have been proposed to mine NSP and most of them only mine NSP from frequent positive sequences, not from infrequent positive sequences (IPS). In fact, many useful NSP can be mined from IPS, just like many useful negative association rules can be obtained from infrequent itemsets. e-NSPFI is a method to mine NSP from IPS, but its constraint is very strict to IPS and many useful NSP would be missed. In addition, e-NSPFI only uses a single minimum support, which implicitly assumes that all items in the database are of the similar frequencies. In order to solve the above problems and optimize NSP mining, a 2-level multiple minimum supports (2-LMMS) constraint to IPS is proposed in this paper. Firstly, we design two minimum supports constraints to mine frequent and infrequent positive sequences. Secondly, we use Select Actionable Pattern (SAP) method to select actionable NSP. Finally, we propose a corresponding algorithm msNSPFI to mine actionable NSP from IPS with 2-LMMS. Experiment results show that msNSPFI is very efficient for mining actionable NSP.

E-MsNFIS: Efficient Negative Frequent Itemsets Mining Based on Multiple Minimum Supports

2013 ◽  
Vol 411-414 ◽  
pp. 386-389 ◽  
Author(s):  
Tian Tian Xu ◽  
Xiang Jun Dong
Keyword(s):  
Association Rules ◽  
Real Life ◽  
Frequent Itemsets ◽  
Negative Association ◽  
Experimental Results ◽  
New Method ◽  
Minimum Support ◽  
Frequent Itemsets Mining ◽  
Negative Association Rules ◽  
Multiple Minimum Supports

Negative frequent itemsets (NFIS) like (a1a2¬a3a4) have played important roles in real applications because we can mine valued negative association rules from them. In one of our previous work, we proposed a method, namede-NFISto mine NFIS from positive frequent itemsets (PFIS). However,e-NFISonly uses single minimum support, which implicitly assumes that all items in the database are of the same nature or of similar frequencies in the database. This is often not the case in real-life applications. So a lot of methods to mine frequent itemsets with multiple minimum supports have been proposed. These methods allow users to assign different minimum supports to different items. But these methods only mine PFIS, doesn’t consider negative ones. So in this paper, we propose a new method, namede-msNFIS, to mine NFIS from PFIS based on multiple minimum supports. E-msNFIScontains three steps: 1) using existing methods to mine PFIS with multiple minimum supports; 2) using the same method ine-NFISto generate NCIS from PFIS got in step 1; 3) calculating the support of these NCIS only using the support of PFIS and then gettingNFIS. Experimental results show that thee-msNFISis efficient.

e-NSPFI: Efficient Mining Negative Sequential Pattern from Both Frequent and Infrequent Positive Sequential Patterns

2017 ◽  
Vol 31 (02) ◽  
pp. 1750002 ◽  
Author(s):  
Yongshun Gong ◽  
Tiantian Xu ◽  
Xiangjun Dong ◽  
Guohua Lv
Keyword(s):  
Association Rules ◽  
Efficient Algorithm ◽  
Optimization Method ◽  
Negative Association ◽  
Experimental Results ◽  
Sequential Pattern ◽  
Sequential Patterns ◽  
Negative Association Rules ◽  
Storage Optimization

Negative sequential patterns (NSPs), which focus on nonoccurring but interesting behaviors (e.g. missing consumption records), provide a special perspective of analyzing sequential patterns. So far, very few methods have been proposed to solve for NSP mining problem, and these methods only mine NSP from positive sequential patterns (PSPs). However, as many useful negative association rules are mined from infrequent itemsets, many meaningful NSPs can also be found from infrequent positive sequences (IPSs). The challenge of mining NSP from IPS is how to constrain which IPS could be available used during NSP process because, if without constraints, the number of IPS would be too large to be handled. So in this study, we first propose a strategy to constrain which IPS could be available and utilized for mining NSP. Then we give a storage optimization method to hold this IPS information. Finally, an efficient algorithm called Efficient mining Negative Sequential Pattern from both Frequent and Infrequent positive sequential patterns (e-NSPFI) is proposed for mining NSP. The experimental results show that e-NSPFI can efficiently find much more interesting negative patterns than e-NSP.

Study on the Software Defects Using Positive and Negative Association Rules Based on Multiple Minimum Supports

2011 ◽  
Vol 474-476 ◽  
pp. 570-576
Author(s):  
Yan Guang Shen ◽  
Jing Shen
Keyword(s):  
Association Rules ◽  
Negative Association ◽  
Software Defects ◽  
Combinatorial Explosion ◽  
Negative Association Rules ◽  
Multiple Minimum Supports

We analyzed the attributes of software defects, and proposed a method of positive and negative association rules based on multiple minimum supports to research on software defects. The application in the software indicated that this method can discover rules of higher quality, fewer errors and conflicts without suffering from combinatorial explosion and missing some less-supported or recessiveness rules.<b></b>

scholarly journals A novel interestingness measure based on fusion model for association rules mining

2021 ◽  
Vol 336 ◽  
pp. 05009
Author(s):  
Junrui Yang ◽  
Lin Xu
Keyword(s):  
Association Rules ◽  
Negative Association ◽  
Fusion Model ◽  
Interestingness Measures ◽  
Association Rules Mining ◽  
Interestingness Measure ◽  
Advantages And Disadvantages ◽  
Measure Model ◽  
Negative Association Rules ◽  
The Difference

Aiming at the shortcomings of the traditional "support-confidence" association rules mining framework and the problems of mining negative association rules, the concept of interestingness measure is introduced. Analyzed the advantages and disadvantages of some commonly used interestingness measures at present, and combined the cosine measure on the basis of the interestingness measure model based on the difference idea, and proposed a new interestingness measure model. The interestingness measure can effectively express the relationship between the antecedent and the subsequent part of the rule. According to this model, an association rules mining algorithm based on the interestingness measure fusion model is proposed to improve the accuracy of mining. Experiments show that the algorithm has better performance and can effectively help mining positive and negative association rules.

A Novel Approach on Negative Association Rules

2011 ◽  
pp. 1425-1430
Author(s):  
Ioannis N. Kouris
Keyword(s):  
Association Rules ◽  
Positive Association ◽  
Negative Influence ◽  
Negative Association ◽  
Association Rules Mining ◽  
Novel Approach ◽  
Negative Effect ◽  
Negative Association Rules ◽  
The Subject ◽  
Definition Of

Research in association rules mining has initially concentrated in solving the obvious problem of finding positive association rules; that is rules among items that exist in the stored transactions. It was only several years after that the possibility of finding also negative association rules became especially appealing and was investigated. Nevertheless researchers based their assumptions regarding negative association rules on the absence of items from transactions. This assumption though besides being dubious, since it equated the absence of an item with a conflict or negative effect on the rest items, it also brought out a series of computational problems with the amount of possible patterns that had to be examined and analyzed. In this work we give an overview of the works having engaged with the subject until now and present a novel view for the definition of negative influence among items.

Sign in / Sign up

Export Citation Format

Share Document