Yet another paper on AI/NLP-powered knowledge graph creation Elsevier’s “Artificial Intelligence in the Life Sciences" is to publish another text from Fraunhofer SCAI with contributions from Kairntech about "A natural language processing system for the efficient updating of highly curated pathophysiology mechanism knowledge graphs”. Lead author Negin Babaiha and her colleagues outline the architecture of … Continue reading Fraunhofer SCAI and Kairntech publish joint work about analysing scientific information
Tag: Machine learning
As reported here, Kairntech has been working together with Fraunhofer SCAI to generate Knowledge Graphs by automatic relation extraction from scientific content. The output is this project was BEL, a graph language, specifically designed for the expression of biomedical facts. Another popular format to express, store and exchange Knowledge Graphs evidently is Neo4J's Cypher: Kairntech … Continue reading Public Neo4J demo with Kairntech-powered content
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!
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
Direct customer feedback In a highly competitive environment, knowing customer complaints and expectations has become a major challenge for all companies. Direct customer feedback has become an increasingly important contributor since the emergence of the Internet. Whether it be results from a speech recording converted into text, a comment from a marketing survey, an incoming … Continue reading Make the Voice of the Customer a Top Priority!
Do you know this situation: You have loads of documents to categorize, no training corpus......and you don't want to ask the experts to build a categorizer for you? Our quick tutorial explains how you can do it on your own: Train your own machine learning model without having to start programming.Download The machines should adapt … Continue reading Quick tutorial: Easy document categorization with Kairntech
Biberach Dec 19 2019 – The German pharma company Boehringer-Ingelheim (BI) and AI software startup Kairntech from Grenoble in France have announced their cooperation on tasks around the analysis of text-based information. The foundation of the cooperation is the licensing of Kairntech’s software platform Sherpa by Boehringer-Ingelheim. “Drug Discovery is a knowledge–driven business”, explains Dr. … Continue reading German Pharma Company Boehringer-Ingelheim licenses AI Platform from Kairntech