# A Geo-Clustering Approach for the Detection of Areas-of-Interest and Their Underlying Semantics +
## 4 Experiments and Results
### Experimental Evaluation
#### 4.2.2 Qualitative Results  
For a qualitative evaluation of the proposed algorithm we chose to focus on user satisfaction. Since the goal is to extract vernacular AOIs, without any prior knowledge, we feel that an appropriate way of evaluation is to assess local residents' satisfaction. We should emphasize that in general, evaluation of tasks aiming at users' satisfaction is known to be a difficult and expensive task, which may involve empirical issues in the process [44]. Having said that, for the sake of evaluating our algorithm, we have conducted a user-centered evaluation by involving 45 real-life users from three (3) academic institutions. More specifically, we involved 25 students from the Technological Educational Institute of Central Greece, Lamia, Greece, 10 students from the Ionian University, Corfu, Greece and 10 students from the National Technical University of Athens, Athens, Greece. These users were to a great extend familiar to Athens city center (all 45 of them are current local residents or Athens is their hometown, even though they currently reside in another city for studies). From the set of performed experiments, we empirically selected cases where the algorithm produces geo-clusters which are intuitively \"close\" to those that consist the user-generated ground truth, which are summarized in Figure 4. This ground truth, illustrated in Figure 5 was empirically and collaboratively created by 10 of the aforementioned users, which did not participate in the actual evaluation. Thus, 35 users were shown the actual results of the algorithm, i.e., the extracted regions and were asked to empirically assess if they overlapped with a substantial amount of regions that are considered to be highly popular to tourists, depending on their personal satisfaction. Moreover, we asked all 45 participants to answer whether what they consider as name of the region was amongst the extracted tags for each, in order to assess the effectiveness of the tag-extraction method that we have presented in Section 3.2. More specifically, these two questions were asked as:  
1. Are you satisfied with the produced vernacular regions? (1: Very dissatisfied; 2: Somewhat dissatisfied; 3: Neither satisfied nor dissatisfied; 4: Somewhat satisfied; 5: Very satisfied)
2. Is the name of the produced vernacular regions included within the top-3 extracted tags? (Yes/No)  
As we may observe, Q1 is a Likert-type question [45]. Since we feel that users may not be divided into groups of age, since all of them are between 19-24 years old and a male-female split is not valid for the problem at hand, we opt not to perform any non-parametric test. Instead, we present some basic statistics to show central tendency (median and mode) and variability (inter-quartile ranges) [46] for each of the clustering that have been presented in Figure 4. Results are depicted in Table 3. Moreover, we illustrate bar charts for each clustering result in Figure 6, while results for Q2 are summarized in Table 4. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \(W_{R}=50\) & \multicolumn{4}{c}{\(W_{R}=100\) m} & \multicolumn{4}{c}{\(W_{R}=200\) m} \\ \hline  & 0.85/5 & 0.85/10 & 0.9/10 & 0.85/5 & 0.85/5 & 0.85/5 & 0.9/10 & 0.9/20 & 0.85/5 & 0.85/5 & 0.85/10 \\  & (T) & (T) & (T) & (T) & (U) & (T) & (T) & (T) & (U) & (T) & (T) \\ \hline AVpGC & 70.18 & 92.40 & 255.05 & 170.79 & 210.57 & 156.99 & 661.4 & 623.07 & 538.89 & 785.75 & 387.61 & 506.05 \\ APGC & 299.10 & 374.22 & 1277.79 & 922.45 & 1071.79 & 606.95 & 4069.13 & 3801.5 & 376.79 & 5422.67 & 1872.54 & 3065.5 \\ ATPGC & 3.16 & 2.79 & 3.46 & 4.14 & 3.57 & 2.70 & 4.6 & 3.14 & 5.58 & 5.83 & 2.85 & 4.36 \\ AGCS & 0.0079 & 0.0070 & 0.0346 & 0.0414 & 0.0357 & 0.0270 & 0.1840 & 0.1257 & 0.2232 & 0.2333 & 0.1139 & 0.1745 \\ APOIpGC & 0.89 & 1.01 & 3.28 & 3.19 & 3.02 & 2.08 & 13.87 & 9.64 & 14.16 & 18.92 & 7.45 & 11.27 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Quantitative Experimental Results assessing the quality of produced geo-clusters.