TeSSI® (Terminology Supported Semantic Indexing) is a state-of-the-art tool that improves upon the existing search and retrieval tools by extracting the meaning out of medical free text and placing the resulting medical ‘concepts’ in the document ind
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FreePharma is a software plug-in that analyzes drug prescription information expressed in free natural language (written or spoken) and structures it automatically for integration in host applications. FreePharma can derive the dose, route, frequency etc.
Annotea is a W3C Semantic Web Advanced Development project that provides a framework for rich communication about Web pages through shared RDF metadata. An RDF model of bookmark classification permits multiple classification systems to be related to each
Text mining and web scraping involves chunk parsing and recognition of named entities (institutions, dates, titles)...The extraction of named entities is mostly based on a strategy that combines look up in gazetteers (lists of companies, cities, etc.) wit
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LinKBase: World's largest formal medical ontology, i.e. a conceptual computer-understandable representation of medicine. Due to its magnitude, formal structure and the fact that it is machine-readable, LinKBase is the only medical knowledge base capable o
As human language is a primary mode of knowledge transfer, a growing integration of language technology tools into semantic web applications is to be expected. Language technology tools will be essential in scaling up the semantic web by providing automat
This Special Issue of JIME will feature nine papers by invited, internationally renowned authors who have previously written about the effect of technology on education, learning and scholarship. Their interests and writing span distance education, higher
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Natural Language Processing (NLP) and Natural Language Understanding (NLU) are technologies that can extract data and information from free text documents for further processing. Language and Computing (L&C) is unique in delivering this level of understan
After analyzing a large amount of social annotations, we found that tags are usually semantically related to each other if they are used to tag the same or related resources for many times. Users may have similar interests if their annotations share many
After analyzing a large amount of social annotations, we found that tags are usually semantically related to each other if they are used to tag the same or related resources for many times. Users may have similar interests if their annotations share many
The semantic web must "explain the meaning of words" to computers. Some semantic technologies use a "bottom up" by embedding semantic annotations (metadata) into web content. "Top down" technologies analyze information without metadata using some form of