Many applications in cognitive science and artificial intelligence utilize semantic similarity
and relatedness to solve difficult tasks such as information retrieval, word sense …

It is well accepted that domain ontologies can support requirement analysis activities,
particularly in detecting inconsistencies and incompleteness of requirement models. These …

Semantic similarity between concepts concerns expressing the degree of similarity in
meaning between two concepts in a computational model. This problem has recently …

AI combined with NLP techniques has promoted the use of Virtual Assistants and have
made people rely on them for many diverse uses. Conversational Agents are the most …

Semantic similarity is very critical in applications that manipulate data across
heterogeneous, autonomous and distributed data sources. It helps connect these data …

Researches about semantic computing are usually evaluated by experiments, lacking
support from the theory of computation. But traditional finite automata are defined on a fixed …

With the trend that the computational process of semantic similarity more and more mimics
the human thought process, it becomes very important to consider the difference between …

The advantages of cloud computing, which include the ability to outsource data processing
to remote servers, have 7ftyhcontributed to the technology's meteoric increase in popularity …

Wikipedia provides rich semantic features eg, text, link, and category structure. These
features can be used to compute semantic similarity (SS) between words or concepts …

This data article compiles the detailed and descriptive experimental data of Wikipedia-based
semantic similarity approach called as Neighbourhood Aggregated Semantic Contribution …