The explosive growth of textual data on the web coupled with the increase on demand for
ontologies to promote the semantic web, have made the automatic ontology construction …

With the widespread growth of data on the Web, the need for efficient methods to get and
arrange valuable information from these big noisy data is increased. The knowledge graph …

With the extensive growth of data that has been joined with the thriving development of the
Internet in this century, finding or getting valuable information and knowledge from these …

Abstract Concepts extraction is the backbone task for an ontology construction system.
Identifying the relevant concepts is considered one of the main challenges of automatic …

In the field of Artificial Intelligence (AI), Deep Learning is a method falls in the wider family of
Machine Learning algorithms that works on the principle of learning. Deep learning models …

Researchers are working towards automation of ontology construction to manage the ever-
growing data on the web. Currently, there is a shift from the use of machine learning …

Identifying entities in text is an important step of semantic analysis. Some entity mentions
comprise a name or description, but many include no information that identifies them in the …

Like many other types of data in the energy industry, well data stored electronically can be
divided into two categories:(1) data stored in relational or object databases that are highly …

Understanding searchers' queries is an essential component of semantic search systems. In
many cases, search queries involve specific attributes of an entity in a knowledge base (KB) …

The digital era has generated a huge amount of data on the identities (profiles) of people,
organizations and other entities in a digital format, largely consisting of textual documents …