Information Measures

As already anticipated in Section 4, the different information measures are also subject of our analysis. Table 5 presents the best results for the different clustering approaches and information measures. It can be concluded from these results that using the PMI or Resnik measures produces worse results on the tourism dataset, while yielding only slightly better results on the finance dataset for the FCA-based approach. It is also interesting to observe that compared to the FCA-based approach, the other clustering approaches are much more sensitive to the information measure used. Overall, the use of the Conditional information measure seems a reasonable choice.

Table 5: Comparison of results for different information measures in terms of F'

	Conditional	PMI	Resnik
FCA
Tourism	44.69%	44.51%	43.31%
Finance	38.85%	38.96%	38.87 %
Complete Linkage
Tourism	36.85%	27.56%	23.52%
Finance	33.35%	22.29%	22.96%
Average Linkage
Tourism	36.55%	26.90%	23.93%
Finance	32.92%	23.78%	23.26%
Single Linkage
Tourism	38.57%	30.73%	28.63%
Finance	32.15%	25.47%	23.46%
Bi-Section-KMeans
Tourism	36.42%	27.32%	29.33%
Finance	32.77%	26.52%	24.00%