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A. Borusan

23.11.2015, 16 Uhr c.t. TU Berlin, EN building, seminar room EN 719 (7th floor), Einsteinufer 17, 10587 Berlin: "On mining trends and recognizing situations" (Olga Strebel, FU Berlin)

Dealing with big data brings many challenges and huge opportunities. In the recent years since big data has been introduced, the research on many interesting issues regarding big data aroused and progressed significantly. Among other research aspects on big data, the analysis, interpretation and therefore useful harvesting of big data remains an interesting issue.
In this talk we focus on trend mining and discuss its potential for situation recognition. Trend mining is based on the idea of harvesting information and knowledge out of trends while bringing an understanding into them. It is defined as the extraction of implicit, previously unknown and potentially useful information from time-ordered texts or data, assuming that this data contains a trend. Basically, a trend template as a knowledge-based approach for trend mining assumes that mining trends with knowledge will help us in understanding a trend.
Moreover, when extending this approach onto different kind of data, we may be able to recognize an upcoming situation that a given trend may cause.