Technology trends analysis and forecasting application based on decision tree and statiscial feature analysis

Abstract

Analyzingmassinformationandsupportingforesightareveryimportanttaskbuttheyareextremely time-consumingwork.Inaddition,informationanalysisandforecastingaboutthescienceandtechnology arealsoverycriticaltasksforresearchers,governmentofficers,businessman,etc.Somerelatedstudies recentlyhavebeenexecutedandsemi-automatictoolshavebeendevelopedactively.Many researchers,annalists,andbusinessmenalsogenerallyusethosetoolsforstrategicdecisionmaking. However,existingprojectsandtoolsarebasedonsubjectiveopinionsfromseveralexpertsandmost oftoolssimplyexplaincurrentsituations,notforecastingnearfuturetrends.Therefore,inthispaper, weproposeatechnologytrendsanalysisandforecastingmodelbasedonquantitativeanalysisandseveral textminingtechnologiesforeffective,systematic,andobjectiveinformationanalysisandforecasting technologytrends.Additionally,weexecuteacomparativeevaluationbetweenthesuggestedmodeland Gartner’sforecastingmodelforvalidatingthesuggestedmodelbecausetheGartner’smodeliswidelyand generallyusedforinformationanalysisandforecasting.