BOOK RECOMMENDATION SERVICE BY IMPROVED ASSOCIATION RULE MINING ALGORITHM
With the extensive application of database system, a mass-circulation historical data is accumulated in university library.We applied data mining technology for discovering useful knowledge in circulation data analysis.There are some shortcomings in mining association rules via Apriori algorithm.This paper introduces two methods for improving the efficiency of algorithm, such as filtrating basic item set, or ignoring the transaction records that are useless for frequent items generated.In order to meet the requirement of personal book recommendation service, we applied the improved algorithm to mine association rules from circulation records in university library.A service model is introduced, and may be used for offering recommendation information to the readers.The recommendation model can also be used in other fields, for example, bookstore, information retrieval system, network reference database, etc.
Book recommendation Service model Data mining Association rule Apriori algorithm
ZHEN ZHU JING-YAN WANG
Foshan University, Foshan 528000, Guangdong, P.R.China
国际会议
2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)
香港
英文
3864-3869
2007-08-19（万方平台首次上网日期，不代表论文的发表时间）