Mining churning behaviors and developing retention strategies based on a partial least squares (PLS) model

In a very competitive mobile telecommunication business environment, marketing managers need a business intelligence model that allows them to maintain an optimal (at least a near optimal) level of churners very effectively and efficiently while minimizing the costs throughout their marketing programs. As a first step toward optimal churn management program for marketing managers, this paper focuses on building an accurate and concise predictive model for the purpose of churn prediction utilizing a partial least squares (PLS)-based methodology on highly correlated data sets among variables. A preliminary experiment demonstrates that the presented model provides more accurate performance than traditional prediction models and identifies key variables to better understand churning behaviors. Further, a set of simple churn marketing programs—device management, overage management, and complaint management strategies—is presented and discussed.     

Partial correlation with copula modeling

We propose a new partial correlation approach using Gaussian copula. Our empirical study found that the Gaussian copula partial correlation has the same value as that which is obtained by performing a Pearson’s partial correlation. With the proposed method, based on canonical vine and d-vine, we captured direct interactions among eight histone genes.     

Application of partial mutual information variable selection to ANN forecasting of water quality in water distribution systems

Recent trends in the management of water supply have increased the need for modelling techniques that can provide reliable, efficient, and accurate representation of the complex, non-linear dynamics of water quality within water distribution systems. Statistical models based on artificial neural networks (ANNs) have been found to be highly suited to this application, and offer distinct advantages over more conventional modelling techniques. However, many practitioners utilise somewhat heuristic or ad hoc methods for input variable selection (IVS) during ANN development.This paper describes the application of a newly proposed non-linear IVS algorithm to the development of ANN models to forecast water quality within two water distribution systems. The intention is to reduce the need for arbitrary judgement and extensive trial-and-error during model development. The algorithm utilises the concept of partial mutual information (PMI) to select inputs based on the analysis of relationship strength between inputs and outputs, and between redundant inputs. In comparison with an existing approach, the ANN models developed using the IVS algorithm are found to provide optimal prediction with significantly greater parsimony. Furthermore, the results obtained from the IVS procedure are useful for developing additional insight into the important relationships that exist between water distribution system variables.     

Disambiguation of partial cognates

Partial cognates are pairs of words in two languages that have the same meaning in some, but not all contexts. Detecting the actual meaning of a partial cognate in context can be useful for Machine Translation tools and for Computer-Assisted Language Learning tools. We propose a supervised and a semi-supervised method to disambiguate partial cognates between two languages: French and English. The methods use only automatically-labeled data; therefore they can be applied to other pairs of languages as well. The aim of our work is to automatically detect the meaning of a French partial cognate word in a specific context.

Verification of bounded Petri nets using integer programming

Model checking based on the causal partial order semantics of Petri nets is an approach widely applied to cope with the state space explosion problem. One of the ways to exploit such a semantics is to consider (finite prefixes of) net unfoldings—themselves a class of acyclic Petri nets—which contain enough information, albeit implicit, to reason about the reachable markings of the original Petri nets. In [19], a verification technique for net unfoldings was proposed, in which deadlock detection was reduced to a mixed integer linear programming problem. In this paper, we present a further development of this approach. The essence of the proposed modifications is to transfer the information about causality and conflicts between the events involved in an unfolding, into a relationship between the corresponding integer variables in the system of linear constraints. Moreover, we present some problem-specific optimisation rules, reducing the search space. To solve other verification problems, such as mutual exclusion or marking reachability and coverability, we adopt Contejean and Devie's algorithm for solving systems of linear constraints over the natural numbers domain and refine it, by taking advantage of the specific properties of systems of linear constraints to be solved. Another contribution of this paper is a method of re-formulating some problems specified in terms of Petri nets as problems defined for their unfoldings. Using this method, we obtain a memory efficient translation of a deadlock detection problem for a safe Petri net into an LP problem. We also propose an on-the-fly deadlock detection method. Experimental results demonstrate that the resulting algorithms can achieve significant speedups.

On Similarity Measures for Multimedia Database Applications

A multimedia database query consists of a set of fuzzy and boolean (or crisp) predicates, constants, variables, and conjunction, disjunction, and negation operators. The fuzzy predicates are evaluated based on different media criteria, such as color, shape, layout, keyword. Since media-based evaluation yields similarity values, results to such a query is defined as an ordered set. Since many multimedia applications require partial matches, query results also include tuples which do not satisfy all predicates. Hence, any fuzzy semantics which extends the boolean semantics of conjunction in a straight forward manner may not be desirable for multimedia databases. In this paper, we focus on the problem of ‘given a multimedia query which consists of multiple fuzzy and crisp predicates, how to provide the user with a meaningful overall ranking.’ More specifically, we study the problem of merging similarity values in queries with multiple fuzzy predicates. We describe the essential multimedia retrieval semantics, compare these with the known approaches, and propose a semantics which captures the retrieval requirements in multimedia databases. Received 13 August 1999 / Revised 13 May 2000 / Accepted in revised form 26 July 2000     

Multi-product multi-chance-constraint stochastic inventory control problem with dynamic demand and partial back-ordering: A harmony search algorithm

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms.     

Mathematical Modelling Of Wreck Events Originated By Dam Collapse

Based on Saint-Venant (shallow water) equations, in this paper the mathematical model of wreck events produced by dam collapse is constructed. A two-layer difference scheme with non-linear regularisation is used for the numerical solution of the aforementioned model. The convergence of this difference scheme in Eulerian variables with non-linear regularisation to the smooth solutions of one-dimensional Saint-Venant equations are considered for a Cauchy problem with periodic (in spatial variables) solutions. The proof of difference scheme convergence is conducted using the energetic method. The existence and uniqueness of the difference scheme solution is proved. That the difference scheme converges in mesh norm $L_2$ with speed $O\lpar h^2\rpar$ in the class of sufficiently smooth solutions of the difference scheme is also proved.     

The convergence of a differential-difference scheme of gas dynamic equations in Lagrangian mass variables

The convergence to a smooth solution of a completely conservative differential-difference scheme of gas dynamic equations in Lagrangian mass variables with sources (sinks) is investigated for the case of the ideal gas. It is proved that for the class of sufficiently smooth solutions of the differential problem the solution of the difference problem converges in the mesh norm L ₂ and that the rate of convergence is O(h ²).     

基于偏微分方程的舌图像去噪研究

在对舌图像的去噪过程中,平滑噪声的同时容易丢失边缘和纹理等细节信息。为此,研究基于偏微分方程的舌图像去噪方法,分别采用中值滤波、高斯滤波、P-M方程、正则化P-M方程以及耦合冲击-复扩散滤波模型,对加噪舌图像进行滤波。比较结果表明,正则化P-M方程更适合舌图像的去噪处理,该方法处理速度快、去噪效果好,且能有效保护图像边缘。