The Design Of Network Recruitment System Based On Data Mining And Implementation

With the rapid development of Internet technology and computer technology, Webapplication development has been growing deeply into all aspects of life in the society.With the increasing amount of data on the Internet, the online recruitment has becomethe main channel of recruitment. Therefore, how to use the massive data of networkrecruitment is a very valuable study. It can find the appropriate information quickly andaccurately, and explore implicit knowledge model. Data mining is a technology toanalyze the large amount of data. It can obtain unknown, internal, and potentially usefulknowledge from vague, noise and random mass data.By combined data mining with Lua-based web spider, this thesis designs aframework of Job information collection and data mining on the network. Through acombination of data analysis Job information, the system follows the design ideas withflexibility, scalability, robustness, and other design principles to network informationcollection processes and Job data mining process. Firstly, it presents techniques andmethods related to the status of international research summary of online recruitmentjob information collection and data mining, including research background andsignificance. Secondly, it discusses current mainstream of data mining techniques andthe key technologies used in this thesis, including Lua scripting language and the Wekadata mining platform. Then, it analyzes and designs the proposed framework system andthe job information collection and data mining system model. It also gives the proposedsystem design principles and objectives, including analysis of the various functionalmodules of the system.Finally, From the results achieved by the system analysis, it shows that the systemcan complete the online recruitment job information collection. It enables data miningfunctionality, and has good practical value.