Prepared by – Mohsin Nadaf, BE IT University of Pune.
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Transcript of Prepared by – Mohsin Nadaf, BE IT University of Pune.
Data Mining in Telecommunications
Prepared by –Mohsin Nadaf, BE ITUniversity of Pune
ContentsIntroductionWhat is Data Mining?Need of Data mining in TelecommunicationCustomer Segmentation and ProfilingTypes of Telecommunication DataData Preparation and ClusteringApplicationsConclusion
IntroductionFast growing IndustryData, the base of TelecommunicationGeneration of tremendous amount of DataKnowledge based Expert-SystemUse of Data Mining and its toolsUncovering hidden informationFuture Decisions
What is Data Mining?Extracting Knowledge hidden in large
volumes of dataIdentifying potentially useful and
understandable data
Technical approaches like Clustering, Data summarization ClassificationAnalyzing ChangesDetecting anomalies
Data Mining in TelecommunicationsTo detect frauds To know customersRetain CustomersWhat products and services yield highest
amount of profit?What are the factors that influence customers
to call more at certain times?
Customer Segmentation and ProfilingCustomer Segmentation
-To describe the process of dividing customers into homogeneous groups on the basis of shared or common attributes (habits, tastes, etc).
Difficulties : -Relevance and quality of data -Intuition -Continuous process -Over-segmentation
Customer Profiling -Describing customers by their attributes, such as age, gender, income and lifestyles
Parameters--Geographic-Cultural and ethnic-Economic conditions -Age and Gender -Attitudes and beliefs -Lifestyle -Knowledge and Awareness
Types of Telecommunication DataCall-Detail DataNetwork DataCustomer Data
Call-Detail Data-average call duration-average call originated/generated-call period-call to/from different area code
Network Data
-Complex configuration of equipments--Error Generation-To support Network Management functions
Customer Data -Database of information of Customers -Name -Age -Address -Telephone type -Subscription Type -Payment History
Data Preparation and ClusteringData preparation
-To be prepared in the required formatTasks:
Discovering and Repairing inconsistent data format
Deleting unwanted data fieldsCombining dataMapping of valuesNormalization of the variables
Clustering-Grouping of Similar things
Cluster Analysis-Organization of objects into groups,
according to similarities among them.
Applications
Marketing/Customer ProfilingFraud DetectionNetwork Fault Isolation
Future TrendsAdditional themes on data miningNew Methods for Complex types of DataInvisible Data mining(mining as a built in
function)Reduction in Human workAdvanced methods in Data mining
CONCLUSIONEarly adopter of Data mining technologyTo detect fraudsHelps to know the CustomerServe them BetterYield more profitReduced much of Human based analysisEssential for Telecommunication companies
REFERENCESData mining in Telecommunication by Gray M. Weiss, Fordham
UniversityCustomer Segmentation and Customer Profiling for a Mobile
Telecommunications Company Based on Usage Behaviour, S.M.H Jansen, July 17, 2007
IJSETT -Applications of Data Mining by Simmi Bagga and Dr. G.N.Singh
A new approach to classify and describe telecommunication services, A.Lehmann1,2, W.Fuhrmann3, U.Trick1, B.Ghita²
Sasisekharan, R., Seshadri, V., Weiss, S. Data mining and forecasting in large-scale telecommunication networks. IEEE Expert 1996; 11(1):37-43.
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