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| Untersuchte Arbeit: Seite: 433, Zeilen: 32-39 |
Quelle: Popp and Poindexter 2006 Seite(n): 23, Zeilen: left col. 5ff |
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| On the other hand, traditional data mining commonly refers to using techniques rooted in statistics, rule-based logic, or artificial intelligence to comb through large amounts of data to discover previously unknown but statistically significant patterns. However, in the application of IDM in the counterterrorism domain, the problem is much harder, because unlike traditional data mining applications, we must, find an extremely wide variety of activities and hidden relationships among individuals. Table 1 gives a series of reasons for why traditional data mining isn’t the same as investigative data mining. | Data mining commonly refers to using techniques rooted in statistics, rule-based logic, or artificial intelligence to comb through large amounts of data to discover previously unknown but statistically significant patterns. However, the general counterterrorism problem is much harder because unlike commercial data mining applications, we must find extremely rare instances of patterns across an extremely wide variety of activities and hidden relationships among individuals. Table 2 gives a series of reasons for why commercial data mining isn’t the same as terrorism detection in this context. |
The source is not mentioned anywhere in the paper. |
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