Abstract To reach the best classification there is a way to use many inaccurate or weak classifiers each of them is specialized for a sub-space in the problem space and using their consensus vote as the final classifier. Many methods have been proposed for classifier ensemble in pattern recognition such as Random Forest which uses a host of decision trees as... To reach the best classification there is a way to use many inaccurate or weak classifiers each of them is specialized for a sub-space in the problem space and using their consensus vote as the final classifier. Many methods have been proposed for classifier ensemble in pattern recognition such as Random Forest which uses a host of decision trees as base classifiers. The paper proposes a heuristic classifier ensemble to improve the performance of learning in the classification. It specially deals with multiclass problems which their aim is to learn the boundaries of each class among many classes. Based on the concept of multiclass problems, the classifiers are divided into two different categories: pairwise classifiers and multiclass classifiers. The aim of a pairwise classifier is to separate one class from another one. Because the pairwise classifiers are just trained to discriminate between two classes, the decision boundaries learned by them are simpler and more effective than those learned by the multiclass classifiers. The two proposed methods are similar to Random Forest method in employing many decision trees and neural networks as base classifiers. For evaluating the proposed weighting methods, both cases of decision tree and neural network classifiers are applied in experimental results. The two proposed ensemble methods are tested on a huge Persian dataset of handwritten digits and it has been shown that the proposed ensemble methods outperforms some other state-of-art ensemble methods. Read More Read Less

Abstract when we look at a face, we easily identify that person’s gender, expression, personality, age, and charisma. Gender classification such as classifying human face is only challenging for computer, but even hard for human in some cases. In this paper a new Novel approach is proposed to recognize gender from the face image. Continuous Wavelet Transforms are used for features... when we look at a face, we easily identify that person’s gender, expression, personality, age, and charisma. Gender classification such as classifying human face is only challenging for computer, but even hard for human in some cases. In this paper a new Novel approach is proposed to recognize gender from the face image. Continuous Wavelet Transforms are used for features selections for each face images of male and female. These selected features will be used to classify the face images of each Gender using Support Vector Machine (SVM). This Paper use ORL database contain 400 images include both Male and Female Gender. The experimental result shows that the proposed approach (Continuous wavelet Transform (1-D) and Linear Discriminate Analysis achieves excellent classification accuracy (100%). Read More Read Less

Abstract The argumentation-based negotiation is among the most recent negotiation approaches. It is studied in several research works which mainly propose general models. The modeling of argumentation-based negotiation mechanism for a specific domain such as e-commerce requires taking into account its specificity with regard to the nature of exchanged information, the various situations of the negotiation parts and advantages and disadvantages... The argumentation-based negotiation is among the most recent negotiation approaches. It is studied in several research works which mainly propose general models. The modeling of argumentation-based negotiation mechanism for a specific domain such as e-commerce requires taking into account its specificity with regard to the nature of exchanged information, the various situations of the negotiation parts and advantages and disadvantages of possible decisions. The main issue in the use of the argumentation-based negotiation is the formalization of the negotiation mechanism. This study aims to propose a semantic web based formalization of argumentation mechanism in e-commerce negotiation; the proposed approach is inspired from the theoretical model developed by Toulmin, S. and the force field analysis technique of Lewin, K. We argue in this paper that our approach synthesizes and improves the general approaches of argumentation. The semantic web based formalization comprises the representation of the elements of arguments, the forces conducting the taken decisions, as well as the protocol of arguments exchange. Semantic web technologies are also employed in the representation of all knowledge which relates to marketplace and its elements (products, buyers and sellers). The electronic marketplace architecture presented in this work is a multi-agent system; the developed agents (Buyer agent and Seller agent) exploit a set of ontologies (MarketOntology, BuyerOntology, SellerOntology, LaptopOntology and ArgumentOntology). Laptops are chosen as a case of study of sold products. Read More Read Less