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Semantic Scholar is a research tool for scientific literature powered by artificial intelligence. It is developed at the Allen Institute for AI and was publicly released in November 2015. [2] Semantic Scholar uses modern techniques in natural language processing to support the research process, for example by providing automatically generated ...
The main academic full-text databases are open archives or link-resolution services, although others operate under different models such as mirroring or hybrid publishers. Such services typically provide access to full text and full-text search, but also metadata about items for which no full text is available.
The Semantic Web, sometimes known as Web 3.0 (not to be confused with Web3 ), is an extension of the World Wide Web through standards [1] set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable. To enable the encoding of semantics with the data, technologies such as Resource Description ...
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Web-based products Search tools. Google Search – a web search engine and Google's core product. Google Alerts – an email notification service that sends alerts based on chosen search terms whenever it finds new results. Alerts include web results, Google Groups results, news and videos. Google Assistant – a virtual assistant.
Semantic analytics, also termed semantic relatedness, is the use of ontologies to analyze content in web resources. This field of research combines text analytics and Semantic Web technologies like RDF. Semantic analytics measures the relatedness of different ontological concepts. Some academic research groups that have active project in this ...
Semantic search seeks to improve search accuracy by understanding the searcher's intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results. Some authors regard semantic search as a set of techniques for retrieving knowledge from richly ...
Ontology learning (ontology extraction, ontology generation, or ontology acquisition) is the automatic or semi-automatic creation of ontologies, including extracting the corresponding domain's terms and the relationships between the concepts that these terms represent from a corpus of natural language text, and encoding them with an ontology language for easy retrieval.