The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Error-reduction sampling (ERS) is a high performing (but computationally expensive) query selection strategy for active learning. Subset optimisation has been proposed to reduce computational expense by applying ERS to only a subset of examples from the pool. This paper compares techniques used to construct the subset, namely random sub-sampling and pre-filtering. We focus on pre-filtering which populates...
Transductive learning is the learning setting that permits to learn from "particular to particular'' and to consider both labelled and unlabelled examples when taking classification decisions. In this paper, we investigate the use of transductive learning in the context of hierarchical text categorization. At this aim, we exploit a modified version of an inductive hierarchical learning framework...
Interpreted languages frequently suffer from higher processing times as compared to compiled approaches. Typically this happens when complex computations are performed. Array DBMSs, which extend database functionality with multidimensional array modeling and query support, find themselves in exactly this situation: queries often involve a large number of operations, and each such operation is applied...
This paper presents G-REX, a versatile data mining framework based on genetic programming. What differs G-REX from other GP frameworks is that it doesn't strive to be a general purpose framework. This allows G-REX to include more functionality specific to data mining like preprocessing, evaluation- and optimization methods, but also a multitude of predefined classification and regression models. Examples...
Constraint-based mining has been proven to be extremely useful. It has been applied not only to many pattern discovery settings (e.g., for sequential pattern mining) but also, recently, on classification and clustering tasks (see, e.g., ). It appears as a key technology for an inductive database perspective on knowledge discovery in databases (KDD), and constraint-based mining is indeed an answer...
Advances in computing and communication has resulted in very large scale distributed environments in recent years. They are capable of storing large volumes of data and often have multiple compute nodes. However, the inherent heterogeneity of data components, the dynamic nature of distributed systems, the need for information synchronization and data fusion over a network and security and access control...
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.