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The data compiled through many Wordnet projects can be a rich source of seed information for a multilingual dictionary. However, the original Princeton WordNet was not intended as a dictionary per se, and spawning other languages from it introduces inheren ...
Modelling the evolution of biological networks is a major challenge. Biological networks are usually represented as graphs; evolutionary events include addition and removal of vertices and edges, but also duplication of vertices and their associated edges. ...
Understanding how evolutionary changes happen requires connecting genotype and phenotype level concepts. This study uses a form of concept map, called Knowledge Integration Map (KIM), as a learning and assessment tool to support and assess connecting conce ...
The purpose of this paper is to present our ideas of applying semantic modelling and ontologies to the issues of products and services. Two selected issues are discussed: i) the collection and reuse of product-service lifecycle data in an IoT-enabled frame ...
The data compiled through many Wordnet projects can be a rich source of seed information for a multilingual dictionary. However, the original Princeton WordNet was not intended as a dictionary per se, and spawning other languages from it introduces inheren ...
The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of features. Some techniques, such as Latent Semantic Analysis (LSA) or Latent D ...
Ontologies provide conceptual abstractions over data, in domains such as the Internet of Things, in a way that sensor data can be harvested and interpreted by people and applications. The Semantic Sensor Network (SSN) ontology is the de-facto standard for ...
The current ICT for manufacturing landscape is characterized by scattered data formats, tools and processes dedicated to different phases in the product lifecycle. Due to the diversity of tools and data formats, manufacturing struggles to cope with new tre ...
Datastores today rely on distribution and replication to achieve improved performance and fault-tolerance. But correctness of many applications depends on strong consistency properties—something that can impose substantial overheads, since it requires coor ...
Recent works on word representations mostly rely on predictive models. Distributed word representations (aka word embeddings) are trained to optimally predict the contexts in which the corresponding words tend to appear. Such models have succeeded in captu ...