Title :
The Application of Association Rules Algorithm on Web Search Engine
Author :
Lu Nan ; Zhou Chun-Guang ; Cui Lai-Zhong
Author_Institution :
Coll. of Comput. & Software, Shenzhen Univ., Shenzhen, China
Abstract :
Aiming at the prevalently concerned mining problem about constructing concept search in current Web search engine area, especially applying the vector space model VSM to Web search mining based on the association rules, this paper provides a highly efficient mining algorithm EARS. The EARS algorithm implements the association rules pruning based on VSM via constructing association library and computing similarity. The EARS stores the frequent itemsets via multi-dimensional linked lists and utilizes the recurrence relation among the frequent itemsets in order to effectively obtain the association rules. We verify the extended function of retrieving and querying on the Web and the results of these experiments indicate that our method is effective and feasible.
Keywords :
Internet; data mining; query processing; search engines; EARS algorithm; Web querying; Web search engine; Web search mining; association library; association rules algorithm; vector space model; Association rules; Data mining; Ear; Educational institutions; Itemsets; Libraries; Partitioning algorithms; Search engines; Software algorithms; Web search; Web mining; association rules; concept search; search engine; vector space model;
Conference_Titel :
Computational Intelligence and Security, 2009. CIS '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5411-2
DOI :
10.1109/CIS.2009.270