Semantic-Based Learning Method for Trend Recognition in Simple Hybrid Information Systems
نویسنده
چکیده
Determination and early detection of emerging trends can be retrieved from numeric data as well as from texts. Using texts for trend mining brings advances for the recognition process. The systematic integration of informaion descriptions and metadata schemes enable the additional semantic analysis of the available information. In this paper, we introduce the issue of trend recognition in information systems based on texts and numeric data. We present our idea of a novel semantic based learning approach which supports the recognition of temporal changing patterns, here called trends, in texts. Since our work is in the early stages, we provide an outline of the direction of our research, providing an overview of the main research issues.
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