II-SDV 2014 Product Presentations Averbis
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Averbis is a company founded in 2007 located in Freiburg im Breisgau, Germany that leverages structured and unstructured information through domain experts and IT specialists in sectors like pharma, health, automotive and publishing. They provide products and technologies like text mining, machine learning and terminology management to help analyze patents and conduct large-scale patent landscaping that can save up to 80% of time compared to manual methods.
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Networking Programme
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Registration
Attendees 2018
Why should you attend
The Venue Hotel
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Exhibition
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II-SDV 2017
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AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
How do you find video when you only have sparse data? While you can wander the stacks (if you can still find open stacks) for inspiration, video either physical or digital, is difficult to discover. Wandering the virtual stacks is, well, virtually impossible. Discovery platforms on the whole have not replicated the inspirational experience of wandering the stacks.
More companies are using archivable video for internal communication of the various research projects, product developments, test results, and more that are being considered, in progress, or completed. Showing how an experiment was conducted can convey considerably more information that is very difficult to communicate via text. How do you find a company video that might be helpful for your project?
A case study is presented of the problems and the solutions that were implemented by a large, multinational chemical company. A suite of content discovery technologies was used including a video to text to tagging system connected to their documents database and automatically indexed using several chemical as well as conceptual systems (rule-based, NLP, inference engine). To build the system and support the manuscript and video submission there is a metadata extraction program which pulls and inserts the metadata into the submission forms so the author can move quickly through that process.
AI-SDV 2022: Copyright Clearance Center
Copyright Clearance Center
A pioneer in voluntary collective licensing, CCC (Copyright Clearance Center) helps organizations integrate, access, and share information through licensing, content, software, and professional services. With expertise in copyright and information management, CCC and its subsidiary RightsDirect collaborate with stakeholders to design and deliver innovative information solutions that power decision-making by helping people integrate and navigate data sources and content assets. CCC recently acquired the assets and technology of Deep SEARCH 9 (DS9), a knowledge management platform that leverages machine learning to help customers perform semantic search, tag content, and discover new insights.
AI-SDV 2022: Lighthouse IP
Lighthouse IP is the world’s leading provider of intellectual property content. The core business of Lighthouse IP is sourcing and creating content from the world’s most challenging authorities. Specialized in IP data, Lighthouse IP provides over 160 countries coverage for patents, over 200 authorities for trademarks and over 90 authorities for designs. Lighthouse IP data is available via several partners. The company is headquartered in Schiphol-Rijk in the Netherlands and has offices in the United States, China, Thailand, Vietnam, Egypt, Indonesia and Belarus. Globally a team of 150 experts works on the creation of this unique data collection.
AI-SDV 2022: New Product Introductions: CENTREDOC
CENTREDOC was created in 1964 as the technical information center of the swiss watchmaking industry. Building on a strong team of engineers, CENTREDOC now offers a complete range of services and solutions for the monitoring of strategic, technological and competitive information. CENTREDOC is also a leader in the research of patent, technical and business intelligence, and offers consulting expertise in the implementation of monitoring solutions.
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
The everyday use of AI-driven algorithms for data search, analysis and synthesis comes with important time savings, but also reveals the need to understand and accept the limitations of the technology. Practical deployments on concrete topics are inevitable to assess and manage the challenges of neuronal network based AI. A workshop report.
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
What if there was a platform where literature, conference abstracts, patents, clinical trials, news, grants and other sources were fully integrated? What if the data would be harmonized, enriched with standardized concepts and ready for analysis? After building our patent analytics platform we didn’t stop dreaming and built our big data analytics platform by semantically integrating text-rich, scientific sources. In my presentation I will talk about what we built and why we built it. And, of course, I will also address the challenges and hurdles along the way. Was it worth it and what comes next? Let’s talk about it!
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AI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
AI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...
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AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...
AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...
AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Machine learning based patent categorization: A success story in...
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
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- 2. ABOUT AVERBIS Founded: 2007 Location: Freiburg im Breisgau Team: Domain- & IT-Experts Focus: Leverage structured & unstructured information Current Sectors: Pharma, Health, Automotive, Publishers & Libraries
- 4. PORTFOLIO PRODUCTS: CORE TECHNOLOGIES: Text Mining Machine Learning Terminology Management Search & Analysis
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- 8. For further questions, please contact Dr. Philipp Daumke philipp.daumke@averbis.com +49 761 - 203 9769 0