9082157
CHAMP: A Prototype for Automated Cellular Churn Prediction
We describe CHAMP (CHurn Analysis, Modeling, and Prediction), an automated system for modeling cellular customer behavior on a large scale. Using historical data from GTE's data warehouse for cellular phone customers, every month CHAMP identifies churn factors for several geographic regions and updates models to generate churn scores predicting who is likely to churn within the near future. CHAMP is capable of developing customized monthly models and churn scores for over one hundred GTE cellular phone markets totaling over 5 million customers.
39681871
Automated Cellular Modeling and Prediction on a Large Scale
We describe CHAMP (CHurn Analysis, Modeling, andPrediction), an automated system for modeling cellularsubscriber churn that is predicting which customerswill discontinue cellular phone service. We describevarious issues related to developing and deployingthis system including automating data access from aremote data warehouse, preprocessing, featureselection, model validation, and optimization toreflect business tradeoffs. Using data from GTE'sdata warehouse for cellular phone customers, CHAMP iscapable of developing churn models customized byregion for over one hundred GTE cellular phone marketstotaling over 5 million customers. Every month churnfactors are identified for each geographic region andmodels are updated to generate churn scores predictingwho is likely to churn in the short term. Learningmethods such as decision trees and genetic algorithmsare used for feature selection and a cascade neuralnetwork is used for predicting churn scores. Inaddition to producing churn scores, CHAMP alsoproduces qualitative results in the form of rules andcomparison of market trends that are disseminatedthrough a web based interface.
12386699
Free parallel data mining
Data mining is computationally expensive. Since the benefits of data mining results are unpredictable, organizations may not be willing to buy new hardware for that purpose. We will present a system that enables data mining applications to run in parallel on networks of workstations in a fault-tolerant manner. We will describe our parallelization of a combinatorial pattern discovery algorithm and a classification tree algorithm. We will demonstrate the effectiveness of our system with two real applications: discovering active motifs in protein sequences and predicting foreign exchange rate movement.
8006585
Linear Transceiver Design for Multiuser MIMO Downlink
An iterative linear transceiver design scheme under sum mean squared error minimization criterion is proposed. By modifying the structure of transceiver, the complex computation of Lagrangian multiplier within traditional MMSE transceiver design can be effectively obviated, and thus the whole system complexity can be greatly reduced. Because the Lagrangian multiplier has analytical solution, transmit preceding matrix also has closed-form solution, and can be solved easily with fixed- point iterations. The receiver filter is worked out independently with MMSE criterion at each terminal, and the downlink signaling of each receive filter from base station is not necessary- Simulations demonstrate that the proposed scheme is effective.
17891437
Call admission control for voice/data integrated cellular networks: performance analysis and comparative study
In this paper, we propose a new call admission control scheme called dual threshold bandwidth reservation, or DTBR scheme. The main novelty is that it builds upon a complete sharing approach, in which the channels in each cell are shared among the different traffic types and multiple thresholds are used to meet the specific quality-of-service (QoS) requirements. We present a detailed comparative study based on mathematical and simulation models, and quantitatively demonstrate that the DTBR is capable of providing the QoS guarantee for each type of traffic, while at the same time leading to much better channel efficiency. We further show that the DTBR scheme with elastic data service can offer both service guarantee and service differentiation for voice and data services, and enhance the bandwidth utilization.
206574982
Battle Damage Assessment based on Bayesian Network
With the quickening rhythm of the war and the complication of battlefield environment,the battle damage assessment(BDA) has had a more important effect on the commander's decision.Because of the complexity of modern battlefield and the uncertainty of battle damage information,it is more and more difficult to determine the damage level of target.Bayesian network is a reasoning and predicting tool coming into vogue only in recent decades.It can correctly reason a problem of interest based on the uncertainty and incomplete information,which is suited to evaluate the battle damage based on the uncertainty and incomplete target damage information.According to the study of BDA based on Bayesian network,the building and updating process of Bayesian network model were discussed.The feasibility and validity of Bayesian network for BDA were analyzed by taking airport runway for example.
2212152
A Model of GIS Virtual Machine
Abstract This paper presents a model of Geographic Information System Virtual Machine. The GIS VM is a software architectural model that facilitates the development of Web-based GIS applications. It is a three-tiered system. Java applets or ActiveX objects, with Web browsers as the container, form the presentation tier that interacts with the user. The core of the GIS VM is the servers in the middle and third tiers. The middle tier includes server components for basic GIS functions and data discovery. The third tire mainly contains the spatial data access server. In addition to these basic servers, the GIS VM includes a model object manager (MOM) that establishes linkages with external models and other application programs. The MOM can also extract metadata about models and carry out the execution process on a user's behalf.