DocumentCode :
719126
Title :
Lexicographic logical multi-hashing for frequent itemset mining
Author :
Chaudhary, Shailza ; Sharma, Abhilasha ; Singh, Ravideep ; Kumar, Pardeep
Author_Institution :
Dept. of Comput. Sci. & Eng., Jaypee Univ. of Inf. Technol., Waknaghat, India
fYear :
2015
fDate :
15-16 May 2015
Firstpage :
563
Lastpage :
568
Abstract :
Mining information from a database is the main aim of data mining since years. The most relevant information which one requires as a result of data mining is getting associations between various attributes. More preciously mining frequent itemset is the most significant step to initiate the mining operation. Most of the algorithms discussed in the literature require multiple scan of the database to get the information on various sub steps of the algorithm which becomes quite computationally extensive. In this paper, we are proposing an algorithm Lexicographic Frequent Itemset Generation (LFIG), which can extract maximum information from a database only in one scan. We will use Lexicographic ordering of attributes and arrange itemsets in multiple hashes which are linked to their logical predecessor.
Keywords :
data mining; text analysis; LFIG; data mining; frequent itemset mining; lexicographic frequent itemset generation; lexicographic logical multihashing; logical predecessor; Association rules; Automation; Computers; Information technology; Itemsets; Association rule mining; Frequent itemsets; LFIG; Lexicographic Order; Multi-Hash;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communication & Automation (ICCCA), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8889-1
Type :
conf
DOI :
10.1109/CCAA.2015.7148467
Filename :
7148467
Link To Document :
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