A COMPACT DATA STRUCTURE BASED TECHNIQUE FOR MINING FREQUENT PATTERNS FROM WEB LOG DATA SET
Akansha Gupta
, Prof. Balwant Prajapat
data mining, frequent pattern mining, frequent closed item sets, data mart, data warehouse.
Frequent pattern mining is top chart research field for young researchers. It has a huge array of real world applications. Although many algorithms, tools, techniques are available for performing the task of frequent pattern mining. Apriori and FP growth are very popular frequent pattern mining techniques. This paper presents an updated methodology for web usage mining. The proposed model is based on the concept of data reduction. Useless data is eliminated from the transaction data base. The experimental results have shown that the proposed updated method is outperforming the existing methods. . In this paper, we have developed a method to discover frequent web item sets from the web transaction database. The proposed method is fast in comparison to older algorithms. Also it takes les main memory space for computation purpose.
"A COMPACT DATA STRUCTURE BASED TECHNIQUE FOR MINING FREQUENT PATTERNS FROM WEB LOG DATA SET", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.2, Issue 6, page no.346 - 349, June-2017, Available :https://ijsdr.org/papers/IJSDR1706052.pdf
Volume 2
Issue 6,
June-2017
Pages : 346 - 349
Paper Reg. ID: IJSDR_170515
Published Paper Id: IJSDR1706052
Downloads: 000347183
Research Area: Engineering
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
