行向量 meaning in Chinese
column vectors
row vector
Examples
- In the preprocessing stage the method of user and session identification often adopt heuristic algorithm for the being of cache and agent . this induce the uncertainty of data resource . the cppc algorithm avoid the limitation and has no use for complicated hash data structure . in this algorithm , by constructing a userld - url revelant matrix similar customer groups are discovered by measuring similarity between column vectors and relevant web pages are obtained by measuring similarity between row vectors ; frequent access paths can also be discovered by further processing of the latter . experiments show the effectiveness of the algorithm . in the fourth part , this thesis bring some key techniques of data mining into web usage mining , combine the characteristic of relation database design and implement a web usage mining system wlgms with function of visible . lt can provide the user with decision support , and has good practicability
本文算法避免了这个缺陷，且不需要复杂的hash数据结构，通过构造一个userid - uel关联矩阵，对列向量进行相似性分析得到相似客户群体，对行向量进行相似性度量获得相关web页面，对后者再进一步处理得到频繁访问路径。实验结果表明了算法的有效性。第四是本文将传统数据挖掘过程中的各种关键技术，引入到对web使用信息的挖掘活动中，结合关系数据库的特点设计并实现了一个具有可广西人学颀士学位论义视化功能的web使用挖掘系统wlgms 。