The European green taxonomies Taxonomy is a word that suddenly appeared with financial investors and the public at large when the European Commission published its own taxonomy on sustainable activities. Let's quickly recall that a taxonomy is a term which originates from biology and that designates the naming in an ordered system that is intended … Continue reading Taxonomy and NLP
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Transformers: the new trend in Artificial Intelligence and NLP Recent progress in NLP (Natural Language Processing) technologies highlights its strong potential for business transformation. While the domain used to be dominated by big players such as Google or Microsoft, smaller organizations are now going mainstream with the collaborative, open source approaches such as Explosion.ai (Spacy) … Continue reading From Hugging Face Transformers to NLP-Powered Applications
We have recently shown you how Kairntech can be used to automate parts of the efforts in vocabulary maintenance: Finding new candidate terms for the update and extension of your vocabularies. We have turned that into a video (5min) that explains the process and shows you how to do this using the software. https://www.youtube.com/watch?v=s3Cqzl67Fms
Introduction Structured vocabularies (thesauri, taxonomies...) play an important role in many applications where complex, large and volatile information needs to be organized and made accessible. A fine example is the famous MeSH thesaurus that facilitates search and access on Medical topics. Enriching scientific content with MeSH terms allows to guarantee that content on a specific … Continue reading Finding new needles in content haystacks: Vocabulary maintenance with AI!
A Knowledge Graph for psychiatric disorders SANKT AUGUSTIN. The Fraunhofer Institute for Algorithms and Scientific Computing SCAI and the software company Kairntech (Grenoble) have created a knowledge graph for psychiatric disorders, especially psychoses. Knowledge graphs allow unstructured texts to be represented in a structured, comparable format. They visualize cause-and-effect models to help medical professionals … Continue reading Fraunhofer SCAI and Kairntech succeed with AI-powered Relation Extraction for Indication-Specific Knowledge Graph assembly
AI no-code NLP platforms change the paradigm In many professions controls are carried out on a random basis. It is a generally accepted practice that an auditor reviewing agreements or an analyst screening litterature proceeds with random checks simply because it is humanly impossible and much too costly to process each individual document. At the … Continue reading Random checks are dead, long live exhaustivity
Introduction Machine Learning approaches in NLP have been shown to be able to solve a wide range of tasks after being trained from scratch on an appropriate training corpus. While this is impressive, it often does not correspond to the demand in many real-world scenarios. Often relevant prior knowledge exists – in the case of … Continue reading Jumpstart your Machine Learning efforts by importing structured knowledge
Introduction Natural language processing (NLP) techniques have made tremendous progress during the last couple of years, thanks notably to algorithms such as Neural Networks which have surpassed traditional approaches using rule-based systems. Examples include Machine Translation (DeepL, Google Translate…) or Speech To Text (Siri…). Information extraction, Text classification, Automatic summarization, Q&A Subcategories of NLP like … Continue reading Make the long road to augmented applications shorter by “do-it-yourself NLP”
Kairntech / DGI webinar on applications of in business contexts: Document categorization and thesaurus-based indexing In the fourth and last session of this series of webinars we explored two more NLP/AI use cases and how they are addressed with the Kairntech software and made available for domain experts and practitioners without the need to engagine … Continue reading Kairntech DGI Webinar of March 24th, 2021
Introduction Named Entity Recognition relates to the extraction of sequences of words from within a document. The technique is mostly used to extract names of people, organisations or places, which are therefore the most typical named entities. However, the term named entity recognition does not capture very well the importance of a fragment of text, … Continue reading Extracting Numbers from Text