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In recent years, due to significant developments in online shopping and the widespread use of e-commerce, competition among companies has increased considerably. As a result, product reviews have become a primary factor in consumers' decision making, which has given rise to a market for fraudulent reviews about real products and services. In this study, the authors propose a model using a multiple...
Tissue classification using computer aided diagnosis can help automated decision making to aid clinical diagnosis. Classification of breast tissue based on spectral features of impedance loci has frequently been done to classify malignant tissue with further requirement of more complex classification methodologies needed to improve the characterisation. In current study, tissue classification is done...
Business intelligence may be defined as a set of mathematical models and analysis methodologies that systematically exploit the available data to retrieve information and knowledge useful in supporting complex decision-making processes. A business intelligence environment offers decision makers information and knowledge derived from data processing, through the application of mathematical models and...
Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact that often available historic data is biased due to discrimination, e.g., when B denotes ethnicity. Using...
Traditional supervised learning assumes that instances are described by observable attributes. The goal is to learn to predict the labels for unseen instances. In many real world applications the values of some attributes are not only observable, but can be proactively chosen by a decision maker. Furthermore, in some of such applications the decision maker is interested not only to generate accurate...
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...
Computer games are attracting increasing interest in the Artificial Intelligence (AI) research community, mainly because games involve reasoning, planning and learning. One area of particular interest in the last years is the creation of adaptive game AI. Adaptive game AI is the implementation of AI in computer games that holds the ability to adapt to changing circumstances, i.e., to exhibit adaptive...
Corpus is the set of language materials which are stored in computers and can use computers to search, query and analyze for enterprise decision-makers. Automated text categorization has been extensively studied and various techniques for document categorization. But based on the current scarcity of Chinese corpus, especially in the field of text categorization, the Chinese categorization corpus is...
Decision tree, as a simple classification algorithm, is an effective tool for mining knowledge rules, and it has been successfully applied in many fields. Based on the selection problems of the expanded attributes, we put forward quasi-linear leaf criterion and data utilization criterion which can recognize the extension ability of attributes, and give a selection model of expanded attributes based...
The taboo state is introduced in environment to discovery sub-goal. Agent samples trajectories from starting state to goal state, which contain different bottlenecks. Then the different tasks are submitted to agent. According to whether the task is accomplished or not, the bottlenecks among them are discovered. The appropriate bottlenecks are selected as sub-goal of options to be constructed according...
Digital Watermarking is an emerging copyright protection technology. The paper presents a new robust watermarking technique based on combining the power of transform domain technique, the Discrete Cosine Transform (DCT) and the data mining technique such as Decision Tree Induction (ID3). The paper focuses on a technique through which the notion of decision tree can be applied on transformed vectors...
Often the only solution for many complex and dynamic real-world situations is a crucial concurrent cooperation and coordination divided into tasks and subtasks, i.e. team behavior [1]. This research focus on such problems under real-time constraints, distributed control and decentralized knowledge. Existent frameworks and simulation systems were designed relying heavily on a priori knowledge of experts...
Credit risk forms an enormous source of losses for money lending institutions. Mechanisms and models to implement early warning credit risk systems have been put in place to aid business risk managers make well-informed decisions. With the establishment of credit reference bureaus (CRB), it's imperative to have a real-time mechanism of collecting data, analyzing it and reporting the knowledge in it...
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive learning. The "selectionist" nature of human decision making indicates the use of an evolutionary paradigm for composing rudimentary neural network units, while the "constructivist" component takes the form...
Under the enormous uncertainty environmental condition, rational and procedures of decision making has been difficult to work effectively. Making decisions by intuition is increasingly viewed as a viable approach at a time of rapid and unprecedented change in the business environment. In this article, we empirical test the proposition that Dane, Pratt(2007) proposed. And, it also expands the research...
Making context based and pertinent clinical knowledge to the point of care that is most appropriate for individuals becomes an unprecedented challenge to bring American closer than ever to the promise of personalized health care. This paper, from the engineering perspective, presents a new conceptual framework that keeps patients in focus and continuously incorporates new knowledge to improve quality...
Neural network tree (NNTree) is a hybrid model for machine learning. Compared with single model fully connected neural networks, NNTrees are more suitable for structural learning, and faster for decision making. To increase the realizability of the NNTrees, we have tried to induce more compact NNTrees through dimensionality reduction. So far, we have used principal component analysis (PCA) and linear...
The mass emergency is an important factor which influents the social stabilization and public security. The nature of it is a kind of articulation of interests. Preventing and dealing with the mass emergency are equally important. To response the mass emergency fast and efficiently, building an emergency management system is necessary. This paper expounds the evolutionary process of mass emergency...
HEARTFAID project is to devise, develop and validate an advanced and innovative technological platform of services and end-user applications aiming at contributing towards the optimization of the clinical management of HF and the reduction of the economic and social costs, by collecting, integrating and processing all types of the above mentioned biomedical data and information. In particular, the...
Models are an integral part of the discipline of Enterprise Architecture (EA). To stay relevant to management decision-making needs, the models need to be based upon suitable metamodels. These metamodels, in turn, need to be properly and continuously maintained. While there exists several methods for metamodel development and maintenance, these typically focus on internal metamodel qualities and metamodel...
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