One of the most important stages in data preprocessing for data mining is feature selection. Real... more One of the most important stages in data preprocessing for data mining is feature selection. Real-world data analysis, data mining, classification and modeling problems usually involve a large number of candidate inputs or features. Less relevant or highly correlated features decrease in general the classification accuracy, and enlarge the complexity of the classifier. Feature selection is a multi-criteria optimization problem
The presence of benchmark problems provides an important stimulus in fields related to the develo... more The presence of benchmark problems provides an important stimulus in fields related to the development of new methodologies. Currently, benchmark data for nature-inspired networks are scarce. To increase the collection of benchmark data, we propose, in this work, a number of interesting and rather difficult managerial and financial decision problems that can be found in the literature. Usually, similar problems are addressed by methodologies belonging to statistics, operations research, mathematical programming, heuristic algorithm implementation, and classical artificial intelligence. We believe that nature inspired intelligence constitutes a challenging alternative for handling these problems effectively. For this reason, we collect formal problem descriptions, related data collections, presentation of existing solutions and comparison of the performance obtained by nature inspired approaches to other existing methodologies.
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2004
The timely production and distribution of rapidly perishable goods is one of the most challenging... more The timely production and distribution of rapidly perishable goods is one of the most challenging logistic problems in the context of supply chain operation. The problem involves several tightly interrelated planning, scheduling and routing problems, each with large combinatorial complexity. From a more practical perspective, the problem calls for a trade-off between risks and returns. To effectively deal with these
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2004
The timely production and distribution of rapidly perishable goods is one of the most challenging... more The timely production and distribution of rapidly perishable goods is one of the most challenging logistic problems in the context of supply chain operation. The problem involves several tightly interrelated planning, scheduling and routing problems, each with large combinatorial complexity. From a more practical perspective, the problem calls for a trade-off between risks and returns. To effectively deal with these
In today’s information-driven global economy, breaking news on economic events such as acquisitio... more In today’s information-driven global economy, breaking news on economic events such as acquisitions and stock splits has a substantial impact on the financial markets. Therefore, it is important to be able to automatically identify events in news items accurately and in a timely manner. For this purpose, one has to be able to mine a wide variety of heterogeneous sources
One of the most important stages in data preprocessing for data mining is feature selection. Real... more One of the most important stages in data preprocessing for data mining is feature selection. Real-world data analysis, data mining, classification and modeling problems usually involve a large number of candidate inputs or features. Less relevant or highly correlated features decrease in general the classification accuracy, and enlarge the complexity of the classifier. Feature selection is a multi-criteria optimization problem
The presence of benchmark problems provides an important stimulus in fields related to the develo... more The presence of benchmark problems provides an important stimulus in fields related to the development of new methodologies. Currently, benchmark data for nature-inspired networks are scarce. To increase the collection of benchmark data, we propose, in this work, a number of interesting and rather difficult managerial and financial decision problems that can be found in the literature. Usually, similar problems are addressed by methodologies belonging to statistics, operations research, mathematical programming, heuristic algorithm implementation, and classical artificial intelligence. We believe that nature inspired intelligence constitutes a challenging alternative for handling these problems effectively. For this reason, we collect formal problem descriptions, related data collections, presentation of existing solutions and comparison of the performance obtained by nature inspired approaches to other existing methodologies.
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2004
The timely production and distribution of rapidly perishable goods is one of the most challenging... more The timely production and distribution of rapidly perishable goods is one of the most challenging logistic problems in the context of supply chain operation. The problem involves several tightly interrelated planning, scheduling and routing problems, each with large combinatorial complexity. From a more practical perspective, the problem calls for a trade-off between risks and returns. To effectively deal with these
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2004
The timely production and distribution of rapidly perishable goods is one of the most challenging... more The timely production and distribution of rapidly perishable goods is one of the most challenging logistic problems in the context of supply chain operation. The problem involves several tightly interrelated planning, scheduling and routing problems, each with large combinatorial complexity. From a more practical perspective, the problem calls for a trade-off between risks and returns. To effectively deal with these
In today’s information-driven global economy, breaking news on economic events such as acquisitio... more In today’s information-driven global economy, breaking news on economic events such as acquisitions and stock splits has a substantial impact on the financial markets. Therefore, it is important to be able to automatically identify events in news items accurately and in a timely manner. For this purpose, one has to be able to mine a wide variety of heterogeneous sources
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Papers by Uzay Kaymak