Augmenting Educational Material with Knowledge Graphs

This approach is supported by the published experience in a similar project [11], where the difficulties of developing a data pre-processing environment are set out for a case

Storage facilities for aquifer geometries, groundwater characteristics and information on groundwater management (ISARM, SADC).

In this context, it has been recognized that to handle the complex knowledge-based scenarios encountered today, such as reasoning over large knowledge graphs, Data- log has to

Unfortunately, current tools for natural language processing do not give us complete accounts of compositionality even at a phrase level: noun-noun compounds have opaque

To measure demonstrated potential domain knowledge (DPDK) we compute the cumulative number of unique entities expressed per month.. The entities are unique since only the

– Wikidata, the knowledge graph of Wikipedia, is natively using a graph-like data model that supports expressive annotations for capturing context [30].. Details are discussed in

To overcome the obstacles mentioned above, it turns out to be appropriate to treat the KG completion problem as an unsupervised relational learning task, and exploit algorithms

In order to enable the discovery and retrieval of suitable datasets and to identify dedi- cated and most efficient preservation strategies for each relevant dataset, we need to