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Now showing items 31-38 of 38
Mining cardinalities from knowledge bases
(Springer Verlag, 2017-08-01)
Cardinality is an important structural aspect of data that has not received enough attention in the context of RDF knowledge bases (KBs). Information about cardinalities can be useful for data users and knowledge engineers ...
Unsupervised learning for understanding student achievement in a distance learning setting
(IEEE, 2017-04-25)
Many factors could affect the achievement of students in distance learning settings. Internal factors such as age, gender, previous education level and engagement in online learning activities can play an important role ...
PandemCap: decision support tool for epidemic management
(NUI Galway, 2017-10-01)
Pandemics or high impact epidemics are one of
the biggest threats facing humanity today. While a complete
elimination of the occurrence of such threats is improbable, it is
possible to contain their impact by efficient ...
Linking knowledge graphs across languages with semantic similarity and machine translation
(MLP 2017, 2017-09-04)
Knowledge graphs and ontologies underpin many natural language processing applications, and to apply these to new languages, these knowledge graphs must be
translated. Up until now, this has been
achieved either by direct ...
From simplified text to knowledge representation using controlled natural language
(2017-04-17)
Knowledge based systems provide means to store data and
perform reasoning on top of it. Controlled Natural Language (CNL) is
considered as an engineered subset of natural language. CNLs aim to
abstract the complexity ...
Biomedical semantic resources for drug discovery platforms
(Springer Verlag, 2017-11-08)
The biomedical research community is providing large-scale
data sources to enable knowledge discovery from the data alone, or from
novel scientific experiments in combination with the existing knowledge.
Increasingly ...
Using drug similarities for discovery of possible adverse reactions
(AMIA, 2017-02-10)
We propose a new computational method for discovery of possible adverse drug reactions. The method consists of two key steps. First we use openly available resources to semi-automatically compile a consolidated data set ...
Grand challenge: Automatic anomaly detection over sliding windows
(Association for Computing Machinery ACM, 2017-06-19)
With the advances in the Internet of Things and rapid generation of
vast amounts of data, there is an ever growing need for leveraging
and evaluating event-based systems as a basis for building realtime
data analytics ...