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 with rules-based systems. Examples include Machine Translation (DeepL, Google Translate…) or Speech To Text (Siri…). Information Extraction, a subcategory of NLP, is also highly impacted. What … 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
Introduction Information extraction tends to target two situations: Extract entities from an existing vocabulary, or Create an extraction model from scratch when there is no existing vocabulary. However, sometimes the situation is a mixture of the two extremes: an incomplete business vocabulary exists but needs to be completed with relevant additional entities of the same type. … Continue reading Bootstrap World Knowledge to extend Business Vocabulary and enhance Knowledge Graphs
Introduction The second session in the DGI Kairntech Webinar series was about Entity Extraction and how user can quickly start their own projects. Please find the presentation (in german) done by Stefan Geissler from Kairntech below: DGI-Webinar-Teil2-NLP-EntityExtractionDownload
Introduction We have arranged a webinar February 10th, 2021 presenting a high-level introduction into Natural Language Processing (NLP) with overview on tasks, demo systems & links to sample code. Please find the presentation (in german) done by Stefan Geissler from Kairntech below: DGI-Kairntech-Webinar-Teil1-NLP-20210210Download
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!
Data Annotation & Active Learning We all heard that "data is the new oil". However, just like its petroleum predecessor, data is of no use until it is processed. One processing step that is often required for unstructured data (e.g. text, images, audio and video files) is data annotation. This is done manually, can require … Continue reading Kairntech & Scaleway Webinar: Thursday, Dec 17, 2020 @ 5:30pm
Introduction We will focus here on the investigation and verification part, which is undoubtedly one of the most important but also one of the most time-consuming for the auditors. However, it is essential to guarantee the sincerity of a company's accounts. This part already has powerful analysis tools for all structured data (mainly numerical numbers). … Continue reading Contract Analysis to Assist the Auditor.