October 2012 Volume 15 Number 4 - Educational Technology ...

shows. However, the benefit of exploring deeper the DBpedia is doubtful. Each extra level implies analyzing a huge
amount of nodes, so the time to obtain the subgraph increases exponentially. For example, if we suppose that each
DBpedia resource has more than 40 relations (e.g. most of dbpedia-owl:Place instances have at least 62
relations), the jump from the third to the fourth level implies reviewing at least 40 4 additional nodes.
Table 6. Summary of the number of nodes and categories retrieved for some LOs during the filtering process
LO id Nodes Categories LO id Nodes Categories
21073 67 52 21133 56 38
21093 72 55 21134 34 23
21094 40 26 21135 38 26
21095 46 18 21136 24 11
21096 15 9 21137 79 58
21113 28 18 21138 197 55
21114 66 52 21139 13 6
21115 3 2 21140 70 41
21116 45 23 21141 8 6
21117 9 4 21142 40 22
21118 40 25 21143 110 80
21119 62 41 21144 62 30
21120 27 13 21145 53 27
21131 14 8 21146 49 33
21132 33 26 21147 70 33
The use of cloud computing and information retrieval techniques for indexing DBpedia are clear ways to improve the
processing time required to annotate the LOs. Nodes may be retrieved faster, and thus we may go deeper in the
search space. However, there is a second factor that prevents to explore in high levels of depth: results quality. In
Mirizzi et al. (2010), authors concluded that 85% of solutions are in the first 3 levels, and that rarely nodes with high
relevance are among nodes above 3 hops.
Figure 5. Screenshot of the lookup service for a query about Chinese
58