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Due to an explosion of data, there has been an increasing demand for scalable machine learning and data mining algorithms in many applications, such as social network analysis, information retrieval, recommendation system, biology applications, multimedia, and e-commerce. The objective of this special issue is to connect academia and industry on the methods and experiences of large scale data analysis. We look for scalable machine learning, data mining algorithms, implementations, frameworks and case studies that target at real and practical scenarios for large datasets. The focus is to identify the real challenges in large-scale data mining and to investigate the scalable methods and practical solutions of the core machine learning and data mining problems with respect to both theoretical and experimental perspectives.
The GWT Window Manager provides a high level windowing system for the GWT applications. It offers a desktop component, dialog features , free floating windows and more. Try it by yourself and feel free to use it, it's free!
Wikipedia is a terrific knowledge resource, and many recent studies in artificial intelligence, information retrieval and related fields used Wikipedia to endow computers with (some) human knowledge. Wikipedia dumps are publicly available in XML format, but they have a few shortcomings. First, they contain a lot of information that is often not used when Wikipedia texts are used as knowledge (e.g., ids of users who changed each article, timestamps of article modifications). On the other hand, the XML dumps do not contain a lot of useful information that could be inferred from the dump, such as link tables, category hierarchy, resolution of redirection links etc.
This is a "tree of all knowledge" category, a top-level place to start when browsing Wikipedia categories for articles. This is the top level in terms of encyclopedia article function and content. It is intended to contain all and only the few most fundamental ontological categories which can reasonably be expected to contain every possible Wikipedia article under their category trees. These categories are: physical entities; biological entities; social entities; and intellectual entities.
An alternative root category, based on a somewhat more detailed initial classification, is Category:Main topic classifications.
Elefant (Efficient Learning, Large-scale Inference, and Optimisation Toolkit) is an open source library for machine learning licensed under the Mozilla Public License (MPL). We develop an open source machine learning toolkit which provides
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