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The collective classification problem for big data sets using MapReduce programming model was considered in the paper. We introduced a proposal for implementation of label propagation algorithm in the network. The method was examined on real dataset in telecommunication domain. The results indicated that it can be used to classify nodes in order to propose new offerings or tariffs to customers.

In this paper, a new method known as Grid Base Classifier was proposed. This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. On the other hand, the eager algorithms classify quickly, but they learn very slowly. The two algorithms were compare...

We propose a focus of attention mechanism to speed up the Perceptron algorithm. Focus of attention speeds up the Perceptron algorithm by lowering the number of features evaluated throughout training and prediction. Whereas the traditional Perceptron evaluates all the features of each example, the Attentive Perceptron evaluates less features for easy to classify examples, thereby achieving signi...

In this paper, we analyze a real-world OVRP problem for a production company. Considering real-world constrains, we classify our problem as multicapacitated/heterogeneous fleet/open vehicle routing problem with split deliveries and multiproduct (MCHF/OVRP/SDMP) which is a novel classification of an OVRP. We have developed a mixed integer programming (MIP) model for the problem and generated tes...

While vendors on the Internet may have enjoyed an increase in the number of clicks on their Web sites, they have also faced disappointments in converting these clicks into purchases. Lack of trust is identified as one of the greatest barriers inhibiting Internet transactions. Thus, it is essential to understand how trust is created and how it evolves in the Electronic Commerce (EC) context thro...

[Measure Twice, Cut Once—Metrics For Online Retailers, 2006, (http://www.techexchange.com/ thelibrary/online_retail_metrics.html)] that once a client made an initial purchase, the buy-to-visit ratio of the client escalates from less than 1% to nearly 21%, the proposed mechanism keeps track of the purchase records of clients and utilizes them to make admission control decisions. We build two has...