AI-SDV 2021: Stefan Geissler - AI support for creating and maintaining vocabularies
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Kairntech provides AI and NLP solutions to facilitate vocabulary creation and maintenance, aimed at making advanced machine learning accessible to domain experts. Their approach integrates automated annotation and existing vocabularies to enhance content analysis, as demonstrated in a case study with client Tecintelli for technology scouting. Kairntech's tools support consistent vocabulary management and reduce the effort needed to maintain large, domain-specific thesauri.
AI-SDV 2021: Stefan Geissler - AI support for creating and maintaining vocabularies
- 1. Kairntech & vocabularies: AI support for creating and maintaining vocabularies AI SDV Oct 4+5, 2021 Stefan Geißler www.kairntech.com
- 2. Introducing Kairntech • Software & Service company with a focus on NLP & AI for industry use cases • Focus on making powerful ML approaches accessible for domain experts (not just programmers and data scientists) • Created in dec 2018, HQ in Grenoble, France • Team with 20+ years of experience in the field (Xerox, IBM, TEMIS, …) • We’ve been attending the SDV for many years, it is a pleasure to be ‘here’ again ☺ Europe’s highest mountain, the Mont Blanc, is visible from many places in the surroundings of Grenoble (~100km)
- 3. Kairntech: Different Approaches to Content Analysis Create NLP models by importing annotated data or adding manual annotation • Entities, Categories, Relations • Users adding their domain expertise • “Active Learning”: Reduces required manual efforts • Immediate feedback • Annotation as Teamwork: Have people cooperate on projects Import of existing vocabularies und thesauri. System will learn the relevant concept. • Integrating your knowledge sources (company- or domain- specific) • Quick creating of respective annotation models • New similar terms? variants? • Import from many different formats Benefitting from public world knowledge : more than 90 mio concepts, multilingual, disambiguated, linked. • Based on wikidata • Regularly updated knowledge source • “Tesla” - inventor or electric car? Kairntech this and countless other ambiguous cases.
- 4. Use case today: AI support in vocabulary management • Thesaurus: Structured vocabulary of terms • Often domain-specific • Important in information retrieval and content analysis • Non-trivial thesauri are often very large (>>10000 terms) • … require considerable effort to build • … and to keep up-to-date as a field evolves • This can be a challenge, especially when working on different subjects at once
- 5. Case study: Kairntech client TecIntelli • https://www.tecintelli.de • Technology and Innovation Intelligence • Based in Stuttgart, Germany • Analysis of large volumes of text content: Web sources, technical documents, scientific literature • Technology scouting, technology monitoring, coaching and consulting • Which technologies exist, which are on the rise, what solutions exist for a given problem? What markets for a given solution?
- 6. Example: Technology scouting for tech SME • Client specializes in building switches / actuators • Realizes their switches are quite fast, in fact faster than competitors’ products • “What else can be done with these? Who else needs faster switches than what is typically sold?” • SME → (often no large research department) • Technology watch project: What are technological fields that need our fast switches? • Literature/market review identified markets and potential clients • An important part of this literature analysis is the identification of key concepts and actors
- 7. Kairntech: AI support for vocabulary maintenance Raw documents Automatic Annotation enriching documents with imported terms Train ML model Broad range of ML algorithms Model application Automatically created suggestions of new terms Wrap AI/NLP/ML into easy-to-use GUI: Domain- specific seed vocabulary
- 8. • Powerful approaches supporting this use case exist (Deep Learning-based entity recognition) • Productive use requires coding and data sciences expertise • Make ML model creation, optimization and application available to domain users without coding experience Point and click AI
- 9. Sample domain: battery technology • Technology field with fast-growing economic potential • Projected yearly worldwide growth of > 12% to reach 279 bn US-$ by 2027 by researchandmarkets.com • Key component in e-mobility, home batteries and portable devices and others • Area of intense research and industrial innovation
- 11. A vocabulary maintenance workflow Seed vocabulary of domain- specific terms Apply vocabulary on document corpus System suggesting new candidates (here new, yet « unknown » types of batteries) Configure Machine Learning experiment
- 12. Searching for new terms • Deep Learning based models take into account various types of clues • Internal structure of candidate term • “… ion …”, “ … Li …”, “ … cell … “, “ … redox …” • Context • „… electrodes of XYZ batteries are often built from …“ • Model architecture allows both types of clues to be taken into consideration • Available ML approaches from fast and relatively simple Conditional Random Fields (CRF) to powerful and computation intensive Deep Learning • No manual rule-writing process required • Large scale pre-trained embeddings and transformer models (such as BERT) are key ingredients
- 13. Full workflow still requires (or benefits from) expert input • Import of seed vocabulary and definition and application of annotator on document content • Fully automatic • Review of annotation results and eventual curation of seed vocabulary and annotations (ambiguities) • Expert input, manual • Consistency is king: “Alzheimer’s” or “Alzheimer’s Disease”? Be consistent in your vocabulary and in your annotations • Definition and application of Machine Learning model training • Fully automatic • Review of newly found terms • Expert decision, manual
- 14. Outcome • Application returned “MVI2 flow battery” and “lithium organosulfor battery” as potential new battery technologies • Both are in fact relatively new approaches in the field (not contained in the seed vocabulary) • Setup allows regular, large-scale scanning of domain-specific content • Time&effort for thesaurus maintenance reduced
- 15. Conclusion • Kairntech: AI/NLP solutions also for non-programmers • Wide range of use cases and languages • Consulting, on-premise packaged software or cloud-based • We love to hear about your use cases Danke! info@kairntech.com www.kairntech.com