Structured vocabularies, thesauri and lexicons are key ingredients for many information management tasks. Creating them however often requires a significant amount of work. Maintaining and extending them often means that the respective manual tasks need to be done on a regular basis in order to prevent the resources from becoming outdated, irrelevant and incomplete. AI has much support to offer for this task. And by wrapping the respective approaches into applications that can be operated by terminologists and domain experts who don't need to be programmers or data scientists themselves, the benefits can be made available to a wide range of users.
Biomax Informatics provides services and software solutions for efficient decision making and knowledge management at the intersection of life sciences, healthcare and information technologies. Biomax facilitates digital transformation within biotech, pharma, agriculture, food and chemical industries as well as research institutes.
Biomax offers a range of standard products, based on the core technology knowledge management technology BioXM™, which are synergistically interrelated.
AILANI™, the Artificial Intelligence LANguage Interface, provides unique semantic search capabilities that catalyze digital change and accelerate the innovation cycle.
NeuroXM™ is the one-stop-shop to decipher brain physiology.
The Clinical Integration System ensures access to real world evidence data, which is critical to effectively and robustly train Artificial Intelligence to support clinical decision support at the point of care.
With more than 20 years of experience and around 50 employees - including numerous life scientists, data scientists and software developers with a scientific background - Biomax is a competent partner.
Founded in 1997, Biomax is ISO 9001 and ISO 27001 certified and is headquartered in Planegg near Munich, Germany.
More info @ www.biomax.com
AI-SDV 2021 - Tony Trippe - The Current State of Machine Learning for Patent ...Dr. Haxel Consult
The use of machine learning in IP activities has increased exponentially over the past five years. At the same time new tools, methods and systems have begun to emerge that seek to make the analysis of patent data easier to accomplish using these techniques. Included in these new developments are a significant number of machine learning systems that have begun coming to market. As these changes continue to occur, it would be useful to review some of the tools, systems, or methods that a patent practitioner has at their disposal. Examples and perspectives on the latest advances in machine learning for IP will be provided. There will also be a tour of ML4Patents.com which is devoted to aggregating content associated with the development of this area.
For over 30 years, Search Technology, Inc. has helped our customers turn information into knowledge. We provide software tools and services that extract more value from patent, scientific, technical and business databases. Our primary product, VantagePoint, helps you rapidly understand and navigate through search results, giving you a better perspective - a better vantage point - on your information. Discover why many of today’s Fortune 100 companies use VantagePoint to help them succeed. VantagePoint is Serious Software for Serious Professionals.
Find more on: http://www.TheVantagePoint.com/
The EXTRA classifier is a scalable solution based on recent advances in Natural Language Processing (NLP). The foundational concept of the EXTRA classifier is transfer learning, a machine learning process that enables the relatively low-cost specialization of a pre-trained language model to a specific task in a specific domain with far fewer training examples compared to standard machine learning solutions.
More specifically, the EXTRA classifier leverages BERT, a well-known pre-trained autoencoding language model that has revolutionized the NLP space in the past few years. BERT provides contextual embeddings, i.e., it provides context-aware vector representations of words that capture semantics far more efficiently than their context-free counterparts.
The EXTRA classifier contains a pre-processing module to cope with the inevitable noise in the output of standard Optical Character Recognition systems. The pre-processed plain text from a source document is then fed into a BERT-based classifier, which is built by extending pre-trained BERT with an additional linear layer trained for classification through a process commonly known as fine-tuning.
We will present preliminary results that confirm some clear benefits with respect to rule-based solutions in terms of classification performance and system scalability.
AI-SDV 2021 - Harald Jenny - Integrated Artificiel Intelligence – A Factory P...Dr. Haxel Consult
AI is not something futuristic any more, but has become an integrated part of our day to day life in IP. Earlier on, AI applications were isolated elements of the searcher’s activities; today, they are fully integrated in the workflow of technology monitoring, allowing to undertake the step from Artificial to Augmented Intelligence.
Patent landscape efforts can get hampered either by voluminous patent search results or the perceived need to manually tag every single feature. It can increase uncertainty, costs, and complexity. Like chemical structure, biosequence, or freedom-to-operate patent searches, patent landscape searches have unique challenges. Delivering custom patent landscape analysis for effective decisions is beyond the skills of most end users. The final patent landscape report can vary depending on the allocated time and the optimal usage of advanced patent analytics tools by professional patent analysts (or by end-users). Many “state of the art” reports only provide patent search results with minimal analysis. Similarly, many automated “instant reports” only provide canned analysis and visuals that are too broad for POV analysis or corporate decision-making. This presentation describes the use of an efficient accelerated, intentional, and multifaceted (AIM™) patent landscape to alleviate these issues. The goal of an AIM™ patent landscape is to intentionally align scope with pending decisions. The results are delivered with appropriate level of analysis, including supporting charts, within an accelerated timeline of 2-3 weeks. AIM™ patent landscape analysis uses experienced patent analysts, a well-defined workflow process, and multiple best-in class patent data search, processing, and visualization tools. AIM™ patent landscapes are ideal in patent portfolio benchmarking efforts and delineating white space opportunities for well-defined projects.
ICIC 2017: Technology Scouting: Decision Support in Strategic Analyses for Te...Dr. Haxel Consult
Stefan Geißler (Expert System Deutschland, Germany)
Tim Schloen (Fraunhofer IAO Stuttgart, Germany)
Trying to keep up to date with developments, trends and opportunities even in narrow domains involves digesting and considering large amounts of textual information and often is beyond the reading capabilities of human experts. Large organisations may be able to cope with this challenge with dedicated analysis teams, but SMEs are overcharge with this information load.
Under the label „Technology Scouting“ we present an approach to employ modern semantic technologies and artificial intelligence to (semi) automate the collection, analysis and reporting of large document collections in a way that allows to derive important insights for technology-driven companies: Which technologies and markets are emerging or moving, how do my clients, partners and competitors operate?
After an introduction to the technological and methodological basis, we present experiences from past industry engagements where this aproach has be applied in production.
Biomax Informatics provides services and software solutions for efficient decision making and knowledge management at the intersection of life sciences, healthcare and information technologies. Biomax facilitates digital transformation within biotech, pharma, agriculture, food and chemical industries as well as research institutes.
Biomax offers a range of standard products, based on the core technology knowledge management technology BioXM™, which are synergistically interrelated.
AILANI™, the Artificial Intelligence LANguage Interface, provides unique semantic search capabilities that catalyze digital change and accelerate the innovation cycle.
NeuroXM™ is the one-stop-shop to decipher brain physiology.
The Clinical Integration System ensures access to real world evidence data, which is critical to effectively and robustly train Artificial Intelligence to support clinical decision support at the point of care.
With more than 20 years of experience and around 50 employees - including numerous life scientists, data scientists and software developers with a scientific background - Biomax is a competent partner.
Founded in 1997, Biomax is ISO 9001 and ISO 27001 certified and is headquartered in Planegg near Munich, Germany.
More info @ www.biomax.com
AI-SDV 2021 - Tony Trippe - The Current State of Machine Learning for Patent ...Dr. Haxel Consult
The use of machine learning in IP activities has increased exponentially over the past five years. At the same time new tools, methods and systems have begun to emerge that seek to make the analysis of patent data easier to accomplish using these techniques. Included in these new developments are a significant number of machine learning systems that have begun coming to market. As these changes continue to occur, it would be useful to review some of the tools, systems, or methods that a patent practitioner has at their disposal. Examples and perspectives on the latest advances in machine learning for IP will be provided. There will also be a tour of ML4Patents.com which is devoted to aggregating content associated with the development of this area.
For over 30 years, Search Technology, Inc. has helped our customers turn information into knowledge. We provide software tools and services that extract more value from patent, scientific, technical and business databases. Our primary product, VantagePoint, helps you rapidly understand and navigate through search results, giving you a better perspective - a better vantage point - on your information. Discover why many of today’s Fortune 100 companies use VantagePoint to help them succeed. VantagePoint is Serious Software for Serious Professionals.
Find more on: http://www.TheVantagePoint.com/
The EXTRA classifier is a scalable solution based on recent advances in Natural Language Processing (NLP). The foundational concept of the EXTRA classifier is transfer learning, a machine learning process that enables the relatively low-cost specialization of a pre-trained language model to a specific task in a specific domain with far fewer training examples compared to standard machine learning solutions.
More specifically, the EXTRA classifier leverages BERT, a well-known pre-trained autoencoding language model that has revolutionized the NLP space in the past few years. BERT provides contextual embeddings, i.e., it provides context-aware vector representations of words that capture semantics far more efficiently than their context-free counterparts.
The EXTRA classifier contains a pre-processing module to cope with the inevitable noise in the output of standard Optical Character Recognition systems. The pre-processed plain text from a source document is then fed into a BERT-based classifier, which is built by extending pre-trained BERT with an additional linear layer trained for classification through a process commonly known as fine-tuning.
We will present preliminary results that confirm some clear benefits with respect to rule-based solutions in terms of classification performance and system scalability.
AI-SDV 2021 - Harald Jenny - Integrated Artificiel Intelligence – A Factory P...Dr. Haxel Consult
AI is not something futuristic any more, but has become an integrated part of our day to day life in IP. Earlier on, AI applications were isolated elements of the searcher’s activities; today, they are fully integrated in the workflow of technology monitoring, allowing to undertake the step from Artificial to Augmented Intelligence.
Patent landscape efforts can get hampered either by voluminous patent search results or the perceived need to manually tag every single feature. It can increase uncertainty, costs, and complexity. Like chemical structure, biosequence, or freedom-to-operate patent searches, patent landscape searches have unique challenges. Delivering custom patent landscape analysis for effective decisions is beyond the skills of most end users. The final patent landscape report can vary depending on the allocated time and the optimal usage of advanced patent analytics tools by professional patent analysts (or by end-users). Many “state of the art” reports only provide patent search results with minimal analysis. Similarly, many automated “instant reports” only provide canned analysis and visuals that are too broad for POV analysis or corporate decision-making. This presentation describes the use of an efficient accelerated, intentional, and multifaceted (AIM™) patent landscape to alleviate these issues. The goal of an AIM™ patent landscape is to intentionally align scope with pending decisions. The results are delivered with appropriate level of analysis, including supporting charts, within an accelerated timeline of 2-3 weeks. AIM™ patent landscape analysis uses experienced patent analysts, a well-defined workflow process, and multiple best-in class patent data search, processing, and visualization tools. AIM™ patent landscapes are ideal in patent portfolio benchmarking efforts and delineating white space opportunities for well-defined projects.
ICIC 2017: Technology Scouting: Decision Support in Strategic Analyses for Te...Dr. Haxel Consult
Stefan Geißler (Expert System Deutschland, Germany)
Tim Schloen (Fraunhofer IAO Stuttgart, Germany)
Trying to keep up to date with developments, trends and opportunities even in narrow domains involves digesting and considering large amounts of textual information and often is beyond the reading capabilities of human experts. Large organisations may be able to cope with this challenge with dedicated analysis teams, but SMEs are overcharge with this information load.
Under the label „Technology Scouting“ we present an approach to employ modern semantic technologies and artificial intelligence to (semi) automate the collection, analysis and reporting of large document collections in a way that allows to derive important insights for technology-driven companies: Which technologies and markets are emerging or moving, how do my clients, partners and competitors operate?
After an introduction to the technological and methodological basis, we present experiences from past industry engagements where this aproach has be applied in production.
AI-SDV 2021 - Klaus Kater - The secret of successful CI: precise targeting + ...Dr. Haxel Consult
New technologies like CRISPR-CAS or mRNA based vaccines require CI teams to constantly screen the market for opportunities and threats. The need for more focused intelligence that is targeted to the company’s strategic plans and faster access to critical information for decision makers has been increasing dramatically: More opportunities can be turned into a competitive advantage and management can avert potential threats before they become problematic. Monitoring early technology development, finding licensing opportunities or acquisition targets as well as quick access to broad clinical trial information and close surveillance of the competition are key disciplines of CI teams in R&D;
AILANI is a novel and unique semantic search enterprise solution for fast, easy and comprehensive knowledge discovery. It combines semantic modelling, ontologies, linguistics and artificial intelligence (AI) algorithms in a self-refining system that delivers results based on inter-related meaning of facts. AILANI not just allows for phrase searches as well as structured queries, it offers its users a unique hybrid natural language question answering system combining machine learning algorithms with semantic network-based "prior knowledge" inference. It integrates seamlessly with existing infrastructure and helps leverage knowledge buried both in decade old data as well as data derived from news feeds and clinical trials providing real-time semantic analysis of breaking news. For the pharmaceutical industry it is critical to stay up to date with the latest clinical trials news for decision-making in drug development. Integration of the relevant data and using ontology-based refiners enables fast and efficient retrieval of information about the clinical competitive landscape.
AI-SDV 2020: Using Transformer technology to build an AI based personal News ...Dr. Haxel Consult
After having successfully implemented a proof of concept in late 2019, DS9 started with one of its customers to implement a pilot for a Deep Learning based personal News Rating system.
The system was initially trained to rate news matching a limited number of typical user profiles. Over time the system would evolve and learn more and more about personal preferences and build user-specific rating models.
This talk looks at the many challenges we overcame during implementation: collecting training data, integrating many diverse news sources, management of many user-specific models and automatic deployment to production.
With IPscreener anyone is able to explore and understand the tech knowledge hidden in patents. By only using a plain text input the semantic AI presents a dashboard of the innovation landscape, identifying similar documents and pointing out relevant paragraphs. Use IPscreener for a smarter way to validating your ideas.
AI-SDV 2020: Implementation of new technology within a big pharma company: Fi...Dr. Haxel Consult
Pharmaceutical companies have always relied on data to support innovation and drive the business. This concept has remained unchanged, despite the fact that today we get it at the speed of light, in an overwhelming volume, and in a global and mostly unstructured way. In order to continue to derive knowledge and insights from that data to support drug discovery and business strategies, integrating AI tools into work processes and acquiring the required skills to do so has become crucial. Although the need is clear, how to implement these new tools is not straightforward in an era of restructuring, divesting, outsourcing, and budget crunching. This talk will focus on creative ways to overcome some of these barriers within a “big pharma” setting with a specific example demonstrating the application of these concepts.
AI-SDV 2021: Jay ven Eman - implementation-of-new-technology-within-a-big-pha...Dr. Haxel Consult
Synonym breaks search! How? Why is this important? What synonym is and how it breaks search will be explained with real-world examples. AI-based solutions are proposed, and relevant standards are identified. How synonym solutions should be used for search are explained. Learn what you can do yourself. Tools help, but it doesn’t have to be complicated, nor expensive. It is as straight forward as setting priorities!
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 2021: Nils Newmann - AI – Who is in control and why is that important?Dr. Haxel Consult
Since the 1950s, AI has been plagued by overpromise and underperformance, particularly at the interface between AI and topical Subject Matter Experts (SMEs). AI has struggled to produce results that SMEs deem effective. As the current hype around the most recent wave of AI recedes, it is time to assess if the new round of research has improved AI’s capacity to help SMEs. This presentation looks at three aspects of current AI research that might actually be useful: Composite AI, Generative AI, and Small Data. These three approaches have the capacity to reduce the distance between AI systems and SMEs by allowing experts to have more local control and input into the behavior of AI systems. This closer interaction has the potential to lead to useful, effective results for SMEs.
Biased Information Retrieval in Pharmaceutical Drug DevelopmentDr. Haxel Consult
Pharmaceutical companies are highly dependent on access to high quality information retrieval. Insufficient gathering and selection of scientific information could potentially impact corporate decision-making in a wrong direction.
To assess the value of external information retrieval services a number of third party information providers were contacted with two information research requests (within inflammatory diseases). The providers were asked to return with search results and search methodologies used. In the first search the interaction with the providers were kept at a minimal level, whereas in the second search the contact, direction, and interaction were increased.
It is concluded that information research results from different providers are variable. The expected increase in inter-homogeneity of results from the different providers could not be confirmed after the second search. The overall overlap of results was 38% for the first search and 33% for the second search, and surprisingly none of the references were found by all providers.
To fully cover the area of interest and to avoid bias it is recommended to perform exhaustive scientific literature searches. Researchers and decision-makers should accept large amounts of results from literature searches and promote initiatives to analyse these results in detail.
Founded in 2004 by a group of business & technology entrepreneurs and inventors, Dolcera is a next generation patent and information analytics company. Our proprietary patent search strategy and domain expertise combined with our game changing AI/ML driven tools like PCS and E-Search enable us to offer top notch patent search and analytics services to our diverse clientele in key decision-making areas of IP strategy & creation, litigation, portfolio analysis, competitive intelligence, product development and licensing.
Our AI- driven tools and services include:
Dolcera PCS – A deep-learning driven superfast patent search engine that offers domain specific Semantic and taxonomy-oriented search capabilities for Patent portfolio analysis, Prior Art, Invalidation and licensing searches.
Dolcera Machine learning for Auto-categorization – The transparent, customizable system solves the problem of human bias or comprehension of a patent when classifying them by leveraging proprietary Dolcera AI/ML. The system gives complete control to the user to deliver highly accurate categorized documents with a quick turn around.
Dolcera Enterprise Search (E-Search) – Dolcera Enterprise Search is a machine learning enabled enterprise-wide search engine integrated with various value added features and smart charts. The application uses patent documents, scientific literature, product information or generally other technical documents inside a company. The system lets users have access to all the related files with minimal clicks to generate actionable insights.
Dolcera ETSI Dashboard – A collection of SEP from various technologies and various specifications updated regularly + PCS (AI driven patent search tool) links the SEPs declared under the specific technical standards & visualize the information for.
Our bespoke services include IP research, technical review, business research and newsletter alerts which help our clients make key strategic decisions in relation to:
Choosing the right technology
Filing & protecting the right IP
Standard mapping and claim charting
Product enhancement
IP, technical & business landscapes
Competitive intelligence
Regulatory landscape
The amalgamation of Dolcera’s AI driven tools, IP services & market research capabilities have time and again assisted our clients in managing their IP & non-IP assets systematically, while enhancing their overall decision-making process.
For further information visit: www.dolcera.com
Our Global presence:
USA: California, Chicago
Europe: Germany, UK
Asia: India, China
The Meeting
Programme
Networking Programme
Speakers 2018
Call for Papers
Registration
Attendees 2018
Why should you attend
The Venue Hotel
Sponsors
Exhibition
Exhibitors
Search Technology VantagePoint
II-SDV Photos Nice 2017
II-SDV 2017
II-SDV 2016
II-SDV 2015
II-SDV 2014
II-SDV 2013
II-SDV 2012
SPEAKERS SINCE 2012
Keep me informed
concerning the II-SDV meeting
ICIC Website
II-PIC Website
Search Technology VantagePoint
For over 30 years, Search Technology, Inc. has helped our customers turn information into knowledge. We provide software tools and services that extract more value from patent, scientific, technical and business databases. Our primary product, VantagePoint, helps you rapidly understand and navigate through search results, giving you a better perspective - a better vantage point - on your information. Discover why many of today’s Fortune 100 companies use VantagePoint to help them succeed. VantagePoint is Serious Software for Serious Professionals.
Deep SEARCH 9 is Data Analysis for the Web.
Combined indexing and search of structured and unstructured sources from the Surface Web, the Deep Web and the Dark Web and corporate data ensure that employees in every part of the organization have access to the information they need without having to use public search engines.
A powerful Application Builder for creating 360° information applications to bring information and analytics together and deliver them to users in a new SEARCH experience.
Advanced content analytics to aggregate, analyze and visualize unstructured (natural language) content to reveal hidden insights and patterns.
Deep SEARCH 9 is the only Web scale analytic search solution that offers corporations a proprietary and anonymous search solution by combining web crawling, content analytics, data linking and search.
More info at: http://www.deepsearchnine.com
Many companies face the challenge of building up a data science team from scratch and it can be hard to figure out how to start. In 2016, I was the first hire of a new data science team, with little infrastructure or strategy in place. Over the years, there were many different challenges for us to solve and mistakes to learn from as the team got more and more mature. This talk is about what I learned about the process of building up a data science team, from both my own experience in the past years and conversations with other data scientists in a similar situation.
Biomax provides computational solutions for better decision making and knowledge management in the life science industry. Biomax helps customers generate value from proprietary and public resources by extracting the knowledge indispensable for efficient data exploration and interpretation. They focus on integrating information to enable a knowledge-based approach to develop innovative life science products. The company supports its customers with a platform that combines software products with knowledge resources, including oncology, nutrigenomics, plant research and functional genomics. With the launch of the NeuroXM Brain Science Suite in 2018 Biomax offers products tailored for the field of connectome research. The new Semantic Searching Platform AILANI provides a corporate-wide knowledge repository accessible for everyone, any time and from anywhere. Biomax’s worldwide customer community includes companies and research organizations that are successful in the areas of drug discovery, diagnostics, fine chemicals, food and plant production.
In 2016, State Street Bank, The EDM Council, Wells Fargo, Dun & Bradstreet and Cambridge Semantics worked together on a proof of concept project to demonstrate a couple of key objectives:
(1) The practicality of using FIBO to harmonize diverse derivative and entity data
(2) The usefulness of FIBO for comprehensive reporting and analytics, both traditional and innovative
IC-SDV 2018: Aleksandar Kapisoda (Boehringer) Using Machine Learning for Auto...Dr. Haxel Consult
Focusing on the significance of targets is one of the key drivers for quality of web search.
Filtering targeted companies based on the significance of their business model for the expected search results was one of our “nice to haves” last year.
Evaluating a number of artificial intelligence approaches based on neural networks, classical machine learning and semantic technologies lead us to a working hybrid approach.
Precision Content™ Tools, Techniques, and Technologydclsocialmedia
This webinar will explore fundamental principles for writing and structuring content for the enterprise. Attendees will learn how to approach information typing for structured authoring for more concise and reusable content.
AI-SDV 2021 - Klaus Kater - The secret of successful CI: precise targeting + ...Dr. Haxel Consult
New technologies like CRISPR-CAS or mRNA based vaccines require CI teams to constantly screen the market for opportunities and threats. The need for more focused intelligence that is targeted to the company’s strategic plans and faster access to critical information for decision makers has been increasing dramatically: More opportunities can be turned into a competitive advantage and management can avert potential threats before they become problematic. Monitoring early technology development, finding licensing opportunities or acquisition targets as well as quick access to broad clinical trial information and close surveillance of the competition are key disciplines of CI teams in R&D;
AILANI is a novel and unique semantic search enterprise solution for fast, easy and comprehensive knowledge discovery. It combines semantic modelling, ontologies, linguistics and artificial intelligence (AI) algorithms in a self-refining system that delivers results based on inter-related meaning of facts. AILANI not just allows for phrase searches as well as structured queries, it offers its users a unique hybrid natural language question answering system combining machine learning algorithms with semantic network-based "prior knowledge" inference. It integrates seamlessly with existing infrastructure and helps leverage knowledge buried both in decade old data as well as data derived from news feeds and clinical trials providing real-time semantic analysis of breaking news. For the pharmaceutical industry it is critical to stay up to date with the latest clinical trials news for decision-making in drug development. Integration of the relevant data and using ontology-based refiners enables fast and efficient retrieval of information about the clinical competitive landscape.
AI-SDV 2020: Using Transformer technology to build an AI based personal News ...Dr. Haxel Consult
After having successfully implemented a proof of concept in late 2019, DS9 started with one of its customers to implement a pilot for a Deep Learning based personal News Rating system.
The system was initially trained to rate news matching a limited number of typical user profiles. Over time the system would evolve and learn more and more about personal preferences and build user-specific rating models.
This talk looks at the many challenges we overcame during implementation: collecting training data, integrating many diverse news sources, management of many user-specific models and automatic deployment to production.
With IPscreener anyone is able to explore and understand the tech knowledge hidden in patents. By only using a plain text input the semantic AI presents a dashboard of the innovation landscape, identifying similar documents and pointing out relevant paragraphs. Use IPscreener for a smarter way to validating your ideas.
AI-SDV 2020: Implementation of new technology within a big pharma company: Fi...Dr. Haxel Consult
Pharmaceutical companies have always relied on data to support innovation and drive the business. This concept has remained unchanged, despite the fact that today we get it at the speed of light, in an overwhelming volume, and in a global and mostly unstructured way. In order to continue to derive knowledge and insights from that data to support drug discovery and business strategies, integrating AI tools into work processes and acquiring the required skills to do so has become crucial. Although the need is clear, how to implement these new tools is not straightforward in an era of restructuring, divesting, outsourcing, and budget crunching. This talk will focus on creative ways to overcome some of these barriers within a “big pharma” setting with a specific example demonstrating the application of these concepts.
AI-SDV 2021: Jay ven Eman - implementation-of-new-technology-within-a-big-pha...Dr. Haxel Consult
Synonym breaks search! How? Why is this important? What synonym is and how it breaks search will be explained with real-world examples. AI-based solutions are proposed, and relevant standards are identified. How synonym solutions should be used for search are explained. Learn what you can do yourself. Tools help, but it doesn’t have to be complicated, nor expensive. It is as straight forward as setting priorities!
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 2021: Nils Newmann - AI – Who is in control and why is that important?Dr. Haxel Consult
Since the 1950s, AI has been plagued by overpromise and underperformance, particularly at the interface between AI and topical Subject Matter Experts (SMEs). AI has struggled to produce results that SMEs deem effective. As the current hype around the most recent wave of AI recedes, it is time to assess if the new round of research has improved AI’s capacity to help SMEs. This presentation looks at three aspects of current AI research that might actually be useful: Composite AI, Generative AI, and Small Data. These three approaches have the capacity to reduce the distance between AI systems and SMEs by allowing experts to have more local control and input into the behavior of AI systems. This closer interaction has the potential to lead to useful, effective results for SMEs.
Biased Information Retrieval in Pharmaceutical Drug DevelopmentDr. Haxel Consult
Pharmaceutical companies are highly dependent on access to high quality information retrieval. Insufficient gathering and selection of scientific information could potentially impact corporate decision-making in a wrong direction.
To assess the value of external information retrieval services a number of third party information providers were contacted with two information research requests (within inflammatory diseases). The providers were asked to return with search results and search methodologies used. In the first search the interaction with the providers were kept at a minimal level, whereas in the second search the contact, direction, and interaction were increased.
It is concluded that information research results from different providers are variable. The expected increase in inter-homogeneity of results from the different providers could not be confirmed after the second search. The overall overlap of results was 38% for the first search and 33% for the second search, and surprisingly none of the references were found by all providers.
To fully cover the area of interest and to avoid bias it is recommended to perform exhaustive scientific literature searches. Researchers and decision-makers should accept large amounts of results from literature searches and promote initiatives to analyse these results in detail.
Founded in 2004 by a group of business & technology entrepreneurs and inventors, Dolcera is a next generation patent and information analytics company. Our proprietary patent search strategy and domain expertise combined with our game changing AI/ML driven tools like PCS and E-Search enable us to offer top notch patent search and analytics services to our diverse clientele in key decision-making areas of IP strategy & creation, litigation, portfolio analysis, competitive intelligence, product development and licensing.
Our AI- driven tools and services include:
Dolcera PCS – A deep-learning driven superfast patent search engine that offers domain specific Semantic and taxonomy-oriented search capabilities for Patent portfolio analysis, Prior Art, Invalidation and licensing searches.
Dolcera Machine learning for Auto-categorization – The transparent, customizable system solves the problem of human bias or comprehension of a patent when classifying them by leveraging proprietary Dolcera AI/ML. The system gives complete control to the user to deliver highly accurate categorized documents with a quick turn around.
Dolcera Enterprise Search (E-Search) – Dolcera Enterprise Search is a machine learning enabled enterprise-wide search engine integrated with various value added features and smart charts. The application uses patent documents, scientific literature, product information or generally other technical documents inside a company. The system lets users have access to all the related files with minimal clicks to generate actionable insights.
Dolcera ETSI Dashboard – A collection of SEP from various technologies and various specifications updated regularly + PCS (AI driven patent search tool) links the SEPs declared under the specific technical standards & visualize the information for.
Our bespoke services include IP research, technical review, business research and newsletter alerts which help our clients make key strategic decisions in relation to:
Choosing the right technology
Filing & protecting the right IP
Standard mapping and claim charting
Product enhancement
IP, technical & business landscapes
Competitive intelligence
Regulatory landscape
The amalgamation of Dolcera’s AI driven tools, IP services & market research capabilities have time and again assisted our clients in managing their IP & non-IP assets systematically, while enhancing their overall decision-making process.
For further information visit: www.dolcera.com
Our Global presence:
USA: California, Chicago
Europe: Germany, UK
Asia: India, China
The Meeting
Programme
Networking Programme
Speakers 2018
Call for Papers
Registration
Attendees 2018
Why should you attend
The Venue Hotel
Sponsors
Exhibition
Exhibitors
Search Technology VantagePoint
II-SDV Photos Nice 2017
II-SDV 2017
II-SDV 2016
II-SDV 2015
II-SDV 2014
II-SDV 2013
II-SDV 2012
SPEAKERS SINCE 2012
Keep me informed
concerning the II-SDV meeting
ICIC Website
II-PIC Website
Search Technology VantagePoint
For over 30 years, Search Technology, Inc. has helped our customers turn information into knowledge. We provide software tools and services that extract more value from patent, scientific, technical and business databases. Our primary product, VantagePoint, helps you rapidly understand and navigate through search results, giving you a better perspective - a better vantage point - on your information. Discover why many of today’s Fortune 100 companies use VantagePoint to help them succeed. VantagePoint is Serious Software for Serious Professionals.
Deep SEARCH 9 is Data Analysis for the Web.
Combined indexing and search of structured and unstructured sources from the Surface Web, the Deep Web and the Dark Web and corporate data ensure that employees in every part of the organization have access to the information they need without having to use public search engines.
A powerful Application Builder for creating 360° information applications to bring information and analytics together and deliver them to users in a new SEARCH experience.
Advanced content analytics to aggregate, analyze and visualize unstructured (natural language) content to reveal hidden insights and patterns.
Deep SEARCH 9 is the only Web scale analytic search solution that offers corporations a proprietary and anonymous search solution by combining web crawling, content analytics, data linking and search.
More info at: http://www.deepsearchnine.com
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- **Spyware**: Software that secretly monitors and collects user information.
### Phishing
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### Man-in-the-Middle (MitM) Attacks
MitM attacks occur when an attacker intercepts and potentially alters communication between two parties without their knowledge. This can lead to the unauthorized acquisition of sensitive information.
### Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) Attacks
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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