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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 ...
LangChain.com. LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization, chatbots, and code analysis.
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.
Semantic AI is a Delaware C-corporation that offers patented, graph-based knowledge discovery, analysis and visualization software technology. Its original product is a link analysis software application called Semantica Pro, and it introduced a web-based analytical environment called the Cortex Enterprise Intelligence Platform, or Cortex EIP.
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 ...
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 ...
e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...
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 ...
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