一种新的Web页面集挖掘方法
A Novel Approach for Web Page Set Mining
摘要：
关联规则挖掘中最耗时的步骤之一是计算数据库中项集的出现频率。哈希表索引方法通过仅扫描事务数据库一次来将事务数据库转换为哈希索引树。每当用户请求任何统一资源定位符（URL）时，请求条目都存储在服务器的日志文件中。本文提出了一种通用的、密集的哈希索引表结构，用于从服务器的日志文件中提取网页集。此哈希表提供有关原始数据库的信息。网页集挖掘（WPs-Mine）提供了原始数据库的完整表示。这种方法适用于稀疏和密集数据分布。哈希表索引支持的Web页面集挖掘表明，其性能始终与访问平面文件上的数据的算法相当，并且往往优于这些算法。增量更新是可行的，无需重新访问原始事务数据库。
英文摘要：
The one of the most time consuming steps for association rule mining is the computation of the frequency of the occurrences of itemsets in the database. The hash table index approach converts a transaction database to an hash index tree by scanning the transaction database only once. Whenever user requests for any Uniform Resource Locator (URL), the request entry is stored in the Log File of the server. This paper presents the hash index table structure, a general and dense structure which provides web page set extraction from Log File of server. This hash table provides information about the original database. Web Page set mining (WPs-Mine) provides a complete representation of the original database. This approach works well for both sparse and dense data distributions. Web page set mining supported by hash table index shows the performance always comparable with and often better than algorithms accessing data on flat files. Incremental update is feasible without reaccessing the original transactional database.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
