By Esteban Zimányi, Ralf-Detlef Kutsche
This e-book constitutes the academic lectures of the 4th eu company Intelligence summer season institution, eBISS 2014, held in Berlin, Germany, in July 2014.
The tutorials awarded the following in a longer and sophisticated structure got by means of popular specialists and canopy themes together with standards engineering for decision-support structures, visible analytics of huge facts units, associated info and semantic applied sciences, supervised type on information streams, and information reuse in huge organizations.
Read or Download Business Intelligence: 4th European Summer School, eBISS 2014, Berlin, Germany, July 6-11, 2014, Tutorial Lectures PDF
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Additional info for Business Intelligence: 4th European Summer School, eBISS 2014, Berlin, Germany, July 6-11, 2014, Tutorial Lectures
For this purpose, we need to count the number of different people per antenna cell and time unit (rather than the total number of calls/CDRs as used in the previous sections). It should be noted again that data have been provided in 2-weeks portions with repeated user IDs across the different portions, therefore limiting time intervals eligible for such analysis in this particular data set due to the inability to distinguish users between data chunks. Multi-perspective Analysis of Mobile Phone Call Data Records 49 Fig.
The darkest blue denotes absence of any calls at those antennas; blue colors correspond to intervals from 1 to 50 calls per day, yellow represents 50–100 calls, orange and reds – more than 100 calls. Fig. 3. Top: dynamics of deciles of counts of call per antenna distributions. 1000, and more than 1000 (darkest red) per day. Note that in the upper image, corresponding interval boundaries are indicated in the scale to the left (Colour ﬁgure online). We can make the following general observations: • Too few data records on Dec 5, 2011 even though CDR time stamps for that day cover the entire 24 h period.
The horizontal event bar immediately below the time graph shows the counts of events over time. The 2D periodic event bar in Fig. 10 (bottom left) shows counts of peak events per 24 h of day (columns) and 14 days of two weeks (rows). The map (bottom-center) and space-time cube (bottom-right) show spatial and spatiotemporal distributions of peak events. We can observe that peak events are frequent in the middle of the day and early in the evening. There are only few exceptions. Thus, several peak events happened during the 15:00–16:00 h interval on Monday and Fridays of the 1st week, and late in the Multi-perspective Analysis of Mobile Phone Call Data Records 51 evening of Saturday of the 2nd week.