Semantic Similarity from Natural Language and Ontology Analysis

Learning semantic similarity for units of language or concepts is crucial not only for numerous tasks in computational linguistics, but also for language understanding and reasoning in the broad context of artificial intelligence. With growing interests and efforts in modeling and computing semantic measures in recent years, we have witnessed much progress in the following two strands of research that approach semantic similarity: corpus-based statistical methods and knowledge-enhanced methods with human knowledge defined in ontologies. This book by Harispe, Ranwez, Janaqi, and Montmain provides a detailed introduction to state-of-the-art research in these two lines of work.