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E-Commerce products often come with rich and tree-structured content information describing the attributes. To well utilize the content information, this study proposed a fuzzy content matching-based recommendation approach to assist e-Commerce customers to choose their truly interested items. In this paper, users' ratings and preferences are represented using fuzzy numbers to remain uncertainties...
Machine learning algorithms, which have been considered as robust methods in different computational fields, assume that the training and test data are drawn from the same distribution. This assumption may be violated in many real world applications like bank failure prediction because training and test data may come from different time periods or domains. An efficient novel algorithm known as Fuzzy...
Creating an applicable and precise financial early warning model is highly desirable for decision makers and regulators in the financial industry. Although Business Failure Prediction (BFP) especially banks has been extensively a researched area since late 1960s, the next critical step which is the decision making support scheme has been ignored. This paper presents a novel model for financial warning...
Recommender systems aim to recommend items that are likely to be of interest to the user. In many business situations, complex items are described by hierarchical tree structures, which contain rich semantic information. To recommend hierarchical items accurately, the semantic information of the hierarchical tree structures must be considered comprehensively. In this study, a new hybrid recommendation...
Creating an applicable and precise failure prediction system is highly desirable for decision makers and regulators in the finance industry. This study develops a new Failure Prediction (FP) approach which effectively integrates a fuzzy logic-based adaptive inference system with the learning ability of a neural network to generate knowledge in the form of a fuzzy rule base. This FP approach uses a...
Genetictic Algorithm (GA) is a widely-used high-efficiency random search and optimization method, which is geneticrated from evolution theory. This paper aims at overcoming the drawbacks of local convergence and not converging well to the globally-optimal solution, which usually exist in the course of solving optimization problems using Basic Genetic Algorithm(GA),and proposes a modified algorithm-...
In saturated markets cross selling offers a number of benefits to companies. While these benefits are recognized by mobile telecommunications companies, many have not fully embraced the concept in practice. This paper focuses on the prediction of cross selling opportunities and presents an innovative approach to forecast cross selling opportunities more effectively. The proposed approach combines...
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