Semantic technology aims to bring meaning and context to computing, with approaches including AI and machine-readable content descriptions. The Web is a key focus, but it can also benefit business and academia. Semantic technology improves computers’ language analysis and content labeling, with potential applications in search engines, speech recognition, online advertising, and academic research. The Semantic Web is a next-generation web where knowledge can be easily manipulated and shared by software agents.
Semantic technology is a concept in computing that aims to bring semantics – the meaning and context behind words and sentences – to the computing world. Numerous approaches have been developed for implementing the concept, ranging from advanced artificial intelligence to formal machine-readable content descriptions. The Web is a key focal point for semantic technology, although it can also benefit business and academia.
While computers excel at mathematical calculations, they struggle with many aspects of human language, particularly semantics. A computer program can defeat even the most skilled humans in a game of chess, but it would fare poorly in a quiz contest against a child because it lacks the ability to accurately interpret the context, meaning, and subtleties of language in the questions. to quiz. This has implications for a wide range of applications and services: without a thorough understanding of context, a search engine may not return accurate results for words with multiple meanings, such as desert and cold, and speech recognition software may struggle with the words that sound the same, sch like “witch” and “which”.
To give computers a deeper insight into the meanings of words and the relationships between them, researchers and proponents of semantic technology have devised a number of approaches, many of which fall into two broad categories: improving computers’ ability to analyze and understand language, and make existing content more machine-readable. Examples of the former approach include advanced artificial intelligence and parallel processing technologies designed to give computers the human-style critical thinking skills needed to discern between relevant and irrelevant content. The second category includes techniques for labeling content on the Web and ontologies — formal descriptions of concepts that may be unique to a specialized domain, such as biology or engineering.
The World Wide Web is a focal point for semantic technology and many hope to see the emergence of a next generation web where knowledge in different forms can be more easily manipulated, discovered and shared by software agents. This Semantic Web, as it has come to be known, was conceived by the forces behind the original Web as far back as the late 1990s. While the full potential of the Semantic Web has yet to be realised, aspects of semantic technology are already commonplace online. For example, many search engines now scan web pages for special types of metadata, a type of information that describes other information. One type of metadata might tell a search engine that a series of numbers is a phone number or physical address, while another type might tag a block of text as a user review of a business or product.
Semantic technology could also benefit a large number of industries and academic disciplines. Online advertisers look for something called semantic targeting to analyze the content of a web page and deliver ads relevant to that content. Large companies and enterprises are eager to eliminate compatibility issues between different computer systems with software and database architectures that better understand the meaning and context of different content. For academics and researchers, discipline-specific ontologies could allow computers to find and bundle relevant searches on very specialized topics, such as a particular protein marker, allowing humans to spend more time analyzing and conducting research rather than to search.
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