Topic-based Multi-document Summarization using Differential
... sentences in target documents is popular approach. To find the best combination of sentences, explicit solution techniques such as integer linear programming, branch and bound method, and so on are usually adopted. However, there is a problem with them in terms of calculation efficiency. So, we appl ...
... sentences in target documents is popular approach. To find the best combination of sentences, explicit solution techniques such as integer linear programming, branch and bound method, and so on are usually adopted. However, there is a problem with them in terms of calculation efficiency. So, we appl ...
Decision making with support of artificial intelligence
... and incompatible database sources is possible but very inefficient. A manager often needs the information very fast to achieve competitive advantage and to solve problems at the level of strategic decision-making. The transformation process of the data to information and to knowledge that is used in ...
... and incompatible database sources is possible but very inefficient. A manager often needs the information very fast to achieve competitive advantage and to solve problems at the level of strategic decision-making. The transformation process of the data to information and to knowledge that is used in ...
Mapping the new frontier: complex genetic disorders
... appropriate mix of genetic and environmental factors using information from a series of families identified by the researcher. Certain assumptions regarding gene mechanism, the frequency of the variant form of the gene, and its suspected penetrance are provide by the researcher who must also specify ...
... appropriate mix of genetic and environmental factors using information from a series of families identified by the researcher. Certain assumptions regarding gene mechanism, the frequency of the variant form of the gene, and its suspected penetrance are provide by the researcher who must also specify ...
Perspectives on Stochastic Optimization Over Time
... of stochastic optimization research in artificial intelligence (AI) and operations research (OR), a process that has been ongoing for more than a decade. In a broad sense, decision making over time and under uncertainty is a core subject in several fields that can perhaps be described collectively a ...
... of stochastic optimization research in artificial intelligence (AI) and operations research (OR), a process that has been ongoing for more than a decade. In a broad sense, decision making over time and under uncertainty is a core subject in several fields that can perhaps be described collectively a ...
How far should AI replace human sense?
... algorithms are being used to instantly search through thousands of cases to identify legal precedents for use in court cases and even to make judgments. In the US, the Missouri Sentencing Commission has developed an Automated Sentencing Application which reportedly calculates the cost of incarcerati ...
... algorithms are being used to instantly search through thousands of cases to identify legal precedents for use in court cases and even to make judgments. In the US, the Missouri Sentencing Commission has developed an Automated Sentencing Application which reportedly calculates the cost of incarcerati ...
Implementing Parallel processing of DBSCAN with Map reduce
... (DBSCAN) is a data clustering algorithm proposed 1996.[1] “It is a density-based clustering algorithm: given a set of points in some space, it groups together points that are closely packed together (points with many nearby neighbors), marking as outliers points that lie alone in low-density regio ...
... (DBSCAN) is a data clustering algorithm proposed 1996.[1] “It is a density-based clustering algorithm: given a set of points in some space, it groups together points that are closely packed together (points with many nearby neighbors), marking as outliers points that lie alone in low-density regio ...
Genetic algorithm
In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.