Final Projct Presntatn

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IntroductionIntroduction

Data mining as well as its synonymsData mining as well as its synonymsknowledge discovery and informationknowledge discovery and informationextraction is frequently referred toextraction is frequently referred to

the literature as the process ofthe literature as the process ofextracting interesting information orextracting interesting information orpatterns from large databases.patterns from large databases.

Major Issues :Major Issues : patternspatterns

interests.interests.


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Profit Mining:Profit Mining:

The aspect of data mining whichThe aspect of data mining which

studies the historical pattern ofstudies the historical pattern oftransactions and facilitate user withtransactions and facilitate user withvalue based decision making tovalue based decision making tomaximize profit.maximize profit.


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Revenue Optimization:Revenue Optimization:

It is a practice that copes withIt is a practice that copes with

deregulation of resources andderegulation of resources andsimultaneously minimizes thesimultaneously minimizes thedilution of revenue from business indilution of revenue from business inorder to maximize the profit.order to maximize the profit.


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The NEED!The NEED!

organizations believe that they areorganizations believe that they areearning the highest revenuesearning the highest revenues

possible from their price andpossible from their price andavailable resource.available resource.

NOTTRUE!!!!


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Product is perishable to great extentProduct is perishable to great extent

Capacity is limited and likely to goCapacity is limited and likely to go

emptyempty

VersusVersus

Market segmentation is achievableMarket segmentation is achievable

Classification of resource is possibleClassification of resource is possible


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There is need of paradigm shift fromThere is need of paradigm shift froman era of broadly averaged, onean era of broadly averaged, one--sizesize--fitsfits--all pricing and herald theall pricing and herald the

dawn of truly price differentiateddawn of truly price differentiatedofferings.offerings.

pricing is not only the mostpricing is not only the mosteffective tool but also the mosteffective tool but also the mostblunt to instigate customers.blunt to instigate customers.


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Literature SurveyLiterature Survey

We have gone throughWe have gone through variousvariousresearch papersresearch papers which deals thewhich deals the

issues which we have took up as ourissues which we have took up as ourproject interest group in additionproject interest group in additionwithwith a few articlesa few articles published atpublished atsome of the very reputed sites.some of the very reputed sites.


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reference1reference1

This discusses aboutThis discusses about gapgap betweenbetweenthe statisticthe statistic--based patternbased pattern

extraction and the valueextraction and the value--basedbaseddecisiondecision--making.making.

Profit mining aims to reduceProfit mining aims to reducethis gapthis gap..


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This paper discusses about the issuesThis paper discusses about the issuesneeded to be handled to optimizeneeded to be handled to optimize

revenues:revenues: predicting requirement ofpredicting requirement of

productsproducts

services failure and demandservices failure and demand

keeping in mind the perishability ofkeeping in mind the perishability ofthe resources.the resources.


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This paper discusses about how aThis paper discusses about how asoftware application model can besoftware application model can bebuild.build.

Escalation Prediction (EP) systemEscalation Prediction (EP) systemthat mines historic defect reportthat mines historic defect reportdatadata and predict the escalation riskand predict the escalation risk

of the defects for maximum netof the defects for maximum netprofit.profit.


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An article that tells about behavior ofAn article that tells about behavior ofa software model for hotel industry.a software model for hotel industry.

The application takes the figureThe application takes the figurebased on customers buying activity,based on customers buying activity,makes a forecast for next few daysmakes a forecast for next few daysand fixes an acceptable bid price.and fixes an acceptable bid price.


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Problem and method descriptionProblem and method description

The area seemed to be hugely vast. AsThe area seemed to be hugely vast. Assimple is the concept of revenuesimple is the concept of revenueoptimization contrarily difficult is itsoptimization contrarily difficult is its

implementation. That is why despiteimplementation. That is why despitephenomenal successphenomenal success

most of these techniques stop short ofmost of these techniques stop short ofthe final objective of data miningthe final objective of data mining--providing possible actions toproviding possible actions tomaximize profit while reducing costsmaximize profit while reducing costs..


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While these techniques are essentialWhile these techniques are essentialto move the data mining result toto move the data mining result tothe eventual application, theythe eventual application, they

nevertheless require great deal ofnevertheless require great deal ofexpert manual and postexpert manual and post--processprocessmined pattern. Therefore we havemined pattern. Therefore we havecontracted our work to the industriescontracted our work to the industrieswhich havewhich have Perishability andPerishability andvariability of value, both invariability of value, both indemand and supply side.demand and supply side.


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Ourtarget!Ourtarget!

The multiplex industryThe multiplex industry

Characteristics:Characteristics:

Ticket loses its value once theTicket loses its value once theshow is started.show is started.

Capacity cannot be increasedCapacity cannot be increased

when demand is high.when demand is high.Every movie is like a new product.Every movie is like a new product.


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AnopportunityAnopportunity

Market segmentation is achievableMarket segmentation is achievablebased on timing and day of thebased on timing and day of theshow.show.

Demand can be somehow predictedDemand can be somehow predictedbased on movie classification.based on movie classification.


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We would be working on theWe would be working on thefollowing aspects to optimizefollowing aspects to optimizerevenues:revenues:

Framework flexibilityFramework flexibility

Time and CostTime and Cost

DemandForecasting andDemand

Forecasting anddynamic pricingdynamic pricing


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ConceivedoutcomeConceivedoutcome

An application/web service that willAn application/web service that will--

forecast the most yieldingforecast the most yieldingdemand scenariodemand scenario

suggest asuggest a dynamic pricingdynamic pricing schemescheme


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ReferencesReferences

1. Profit Mining1. Profit Mining

Senqiang Zhou, Ke WangSenqiang Zhou, Ke Wang, Simon Fraser University, Canada, Simon Fraser University, Canada

2. Optimizing Revenues,2. Optimizing Revenues,The yield management wayThe yield management way

Mr. Mihir biswasMr. Mihir biswas,, Head IT& Systems,EHead IT& Systems,E--cityentertainmentscityentertainments

Mr. K.C. GandhiMr. K.C. Gandhi,, DGM, Indian Airlines and othersDGM, Indian Airlines and others3. Maximum ProfitMiningandIts Applicationin Software3. Maximum ProfitMiningandIts Applicationin Software

DevelopmentDevelopment

Charles X. Ling1, Victor S. Sheng1, Tilmann Bruckhaus2, NazimCharles X. Ling1, Victor S. Sheng1, Tilmann Bruckhaus2, Nazim

H. Madhavji1 Department of Computer Science,H. Madhavji1 Department of Computer Science,

The University of Western Ontario.The University of Western Ontario.4.Data Mining foractionable knowledge,4.Data Mining foractionable knowledge,

Zengyou he, Xiaofei xu, Shengchung Deng, Dept OF CSE, HerbingZengyou he, Xiaofei xu, Shengchung Deng, Dept OF CSE, HerbingInstitute ofTechnology.Institute ofTechnology.


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ReferencesReferences


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Thank youThank you

Presented by:Presented by:Gaurav(030508)Gaurav(030508)

Prashant(030462)Prashant(030462)

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Final Projct Presntatn