關(guān)聯(lián)規(guī)則挖掘在人力資源網(wǎng)站中的研究與實(shí)現(xiàn).pdf

1、北京交通大學(xué)碩士學(xué)位論文關(guān)聯(lián)規(guī)則挖掘在人力資源網(wǎng)站中的研究與實(shí)現(xiàn)姓名：杜靖申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：軟件工程指導(dǎo)教師：劉渭濱201206AbstractAssociationRuleMining(ARM)isamethodwhichisusedtoprocesshugeamountofdatatodiscovervaluablerelationshipsamongdataitemsSuchmethodcanfindimplicit，unk

2、nown，andpotentialvaluableknowledgewhichusermightbeinterestedinARMisoneofmostpopularresearchdirectionsinthedomainofdatamining，whichhasgreatresearchvalueandbroadapplicationprospectsThroughanalyzingexistingdomestichumanreso

3、urcewebsitesandweakpointsofresearchingonstatisticdataofthesewebsites，thispaperhasproposedARMtoanalyzestatisticdataofwebsitetendencyMeanwhile，basedonthefactthatusingassociationrulescalleffectivelyfindoutvaluablerelationsh

4、ipamongdatathethesisintroducesARMintotheprocedureofanalyzingstatisticdataofhumanresourcewebsite，andimprovesthe‘‘Apriori’’algorithmfromtheaspectsofloweringthenumberofcandidatesetandtimeofscanningdatabaseThen，theimproved“A

5、priori’’algorithmisimplementedonthetestplatformofwebsitetocounthumanresourcewebsitetrendandrealizecorrespondingfunctionsThemajorworkoftheauthorincludes：1)Improvingthe“Apriori”algorithmwhichaddsdatapreprocessingprocedurea

6、ndneweventgrouptosolveproblemssuchastoolargecandidatesetandmultipledatabasescanning，andmakingcomparisonbetweentheoriginalalgorithmandtheimprovedalgorithmComparedwiththeoriginalalgorithm，theimproved“Apriori’’algorithmhass

7、avedcomputingtimeandmemo巧spacewhichareusedbytheoriginalalgorithmtoproceedspartofcandidatesetsTheimprovedalgorithmalsoincreasesminingefficiencyofassociationrelationshiprules，andsolvesmajorproblemsoftheoriginal‘‘Apriori”al

8、gorithm2)Smdyinghumanresourcewebsitemodelwhichisbasedonusers，positions，andinterviewquestions，whichutilizeshighlyscalableLAMP(Linux州嬸acheMysqlPHP)frameworkandDiscuzsystemThewebsitemodelisproposingNemomodulewhichseparatest

9、heartprogramfromtheapplicationdesign，andhasfmaUyrealized‘‘interviewencyclopediawebsite”3)Realizingthehumanresourcewebsitetrendpredictionwhichisbasedontheimproved“Apriori”algorithmandwebsiteapplicationenvironment，andtakin