If you’re asking yourself what is semantic technology? you are already, in fact, using semantics.
The word “semantic” refers to meaning in language. Semantic technology leverages artificial intelligence to simulate how people understand language and process information.
By approaching the automatic understanding of meanings, semantic technology overcomes the limits of other technologies.
Why artificial intelligence?
If we want a machine to understand our language, we have to go beyond the logic of the calculation that typically is associated with computers. Cognitive actions are the opposite of structured: everyday language can contain endless amounts and types of information, expressed in many different ways. More “intelligent” tools, such as cognitive computing systems based on semantics, have been gradually introduced to overcome the limitations of other technologies, offering users easier interaction with machines and easier access to information. A computer can never fully substitute a human and semantic technology is not perfect; however, semantics leverages specific artificial intelligence algorithms to successfully perform specific cognitive tasks that approach the automatic understanding of meanings. This is what differentiates semantics from other technologies because it is able to simulate how people read, understand language and process information. (To learn more about natural language processing, check out the post “Natural Language Processing Techniques”.)
What semantic technology does and how it works
Regarding the approach, semantic technology reads and tries to understand language and words in its context. Technically speaking, this approach is based on different levels of analysis: morphological and grammatical analysis; logical, sentence and lexical analysis, in other words: natural language analysis.
In the case of Cogito, its criteria for semantic technology involves different integrated elements. The most important elements are the following:
- parser carries out morphological, grammatical and syntactical analysis of the sentence
- lexicon recognizes words and all of their meanings
- memory keeps track of analysis outcomes
- knowledge represents real world knowledge
- content representation is text content in the form of a conceptual and cognitive map
The lexicon involves the so-called “semantic network.” At Expert System, we call our set of semantic networks “Sensigrafo.” It is not an average dictionary but resources that have been optimized for programmatical use, where word forms are knots linked to each other by multiple links denoting semantic or lexical relations.
Why semantic technology
As humans, understanding our everyday language and the meanings of words is easy. Transferring these same capabilities to a machine is not so simple.
As our CTO at Expert System always says: “Learning takes time, and the same goes for a computer. There are no shortcuts nor magic formulas: learning a language is difficult and even automatic processes require time and labor.” (Marco Varone, Computers Go to Semantic School)
However, in the big data era where unstructured information accounts for 80% of all information, having a technology that can understand and extract knowledge from this data is not a nice-to-have; it is fundamental for being competitive in any market, as information is one of the most powerful forces changing the way business is done.
To learn more about Expert System’s semantic technology, Cogito, visit https://devexpertai.wpengine.com/it/cogito/
