Semantic Similarity and Artificial Intelligence

There are many applications within the field of information retrieval, which have aroused great interest in recent years. These applications, mostly belonging to the area of Computer Linguistics, Information Retrieval and Artificial Intelligence, sometimes use a common procedure for their resolution: the calculation of the semantic similarity between two terms. This semantic similarity is used for the resolution of multiple problems in a wide variety of computational fields. To name just a few: word disambiguation, error detection, and correction writing, text classification, link discovery, search engines, etc.

The widespread use of semantic similarity is demonstrated by the large number of existing measures used for their calculation. The most relevant measures can be divided into those that use taxonomies or hierarchical structures, those using corpus and those using search engine results. Some measures use a combination of both. The so-called semantic similarity aggregation. And this is usually done by using soft computing techniques.