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| Title: |
Modern Applications of Machine Learning |
| Author(s): |
G. Tzanis, I. Katakis, I. Partalas, I. Vlahavas.
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| Availability: |
Click here to download the PDF (Acrobat Reader) file.
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| Keywords: |
Machine Learning, Applications.
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| Appeared in: |
Proceedings of the 1st Annual SEERC Doctoral Student Conference, Thessaloniki, Greece, 2006.
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| Abstract: |
Machine learning is one of the older areas of artificial intelligence and concerns the study of computational methods for the discovery of new knowledge and for the management of existing knowledge. Machine learning methods have been applied to various application domains. However, in the few last years due to various technological advances and research efforts (e.g. completion of the Human Genome Project, evolution of the Web), new data have been available and consequently new domains where machine learning can be applied have been arisen. Some of these modern applications are learning from biological sequences, learning from email data, and learning in complex environments such as Web. In this paper we present the above three application domains as well as some recent efforts, where machine learning techniques are applied in order to analyze the data provided by these domains. |
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