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Text Categorization (TC) is an important component in many information organization and information management tasks. In many TC applications, the case-base grows at a fast rate and this causes inefficiency in the case retrieval process. Using Case-Base Maintenance learning via the GC (Generalization Capability) algorithm, which can reduce the case number into KNN algorithm, can improve efficiency...
Text categorization (TC) is an important component in many information organization and information management tasks. Two key issues in TC are feature coding and classifier design. The Euclidean distance is usually chosen as the similarity measure in K-nearest neighbor classification algorithm. All the features of each vector have different functions in describing samples. So we can decide different...
K-nearest neighbor (K-NN) algorithm is a classification method based on statistical theory. In this algorithm the Euclidean distance is usually chosen as the similarity measure, which usually relates to all attributes. Accordingly one practical issue in applying K-NN algorithm is that the distance between instances is calculated based on all attributes of the instance. One interesting approach to...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.