An Efficient Approach for Candidate Set Generation
AbstractWhen Apriori was first introduced as an algorithm for discovering association rules in a database of market basket data, the problem of generating the candidate set of the large set was a bottleneck in Apriori's performance, both in space and computational requirements. At first, many unsuccessful attempts were made to improve the generation of a candidate set. Later, other algorithms that out performed Apriori were developed that generate association rules without using a candidate set. They used the counting property of association rules instead of generating the candidate set as Apriori does. However, the Apriori concept has been used in many different areas other than counting market basket items, and the candidate generation problem remains a bottleneck issue. The approach described here improves the overall time and space requirements by eliminating the need for a hash table/tree of formation for the candidate set.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by World Scientific Publishing Co. Pte. Ltd. in its journal Journal of Information & Knowledge Management.
Volume (Year): 04 (2005)
Issue (Month): 04 ()
Contact details of provider:
Web page: http://www.worldscinet.com/jikm/jikm.shtml
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tai Tone Lim).
If references are entirely missing, you can add them using this form.