基于数据挖掘的智能化OPAC系统设计

Intelligent OPAC System Design Based on Data Mining

针对传统OPAC系统缺乏智能应用的实际,在Microsoft SQL Server 2005 Data Mining和Vi sual Studio2005环境中,设计开发一个基于数据挖掘推荐引擎的智能化OPAC系统,系统能够在读者检索图书的同时,推荐与其密切相关的系列书目信息,深入引导读者借阅行为。同时,提出一种基于划分思想的改进型Apriori关联规则算法,通过系统开发证实了改进算法的有效性。

In view of the fact that traditional OPAC（Online Public Access Catalog） system lacks intelli- gence application, in Microsoft SQL Server 2005 Data Mining and Visual Studio2005 environment, the pa- per design and development a intelligent OPAC system based on data mining recommendation engine. The system can recommend series of bibliographic information associated with the retrieve results when readers submit a query, in-depth Guide to readers＂ borrowing behaviors. The paper focus on the Apriori association rules mining algorithm, presents an enhanced method based on Vertical Data Partitioning con- ditioning regimens, which can effectively reduce the number of data to improve the original Apriori algo- rithm performance. The result of experiments on historical Book-borrowing Records shows that the algo- rithm presented is efficient and robust.