II-SDV 2016 Centredoc

•

0 j'aime•734 vues

Dr. Haxel Consult

Internet

CENTREDOC
CENTREDOC
in 4 numbers
52
32
15
150
CENTREDOC has been created 52
years ago by the Swiss Watch
Industry as a shared ressource for
Technology Monitoring.
CENTREDOC is a cooperative with 32
members. Some of them: Swatch
Group, Rolex, Cartier, Patek Philippe,
TAG Heuer, Nestlé and the CSEM.
CENTREDOC counts15 collaborators
specialised in technology monitoring
and strategic innovation support
services.
CENTREDOC annualy serves more
than 150 customers. Some of them :
Nestlé, Swatch, Essilor, Sanofi, Scott
Sport and Armasuisse.
Image: www.erlebnis-schweiz.com

CENTREDOC
Business Intelligence (BI)
Swiss Center for Search, Analysis and Synthesis of Information
High quality multiple data sources
Advanced processing capabilities
Analysis & Key information extraction
BI Competitive advantage for growth and long term stability

CENTREDOC
Search Monitor Collaborate Share

CENTREDOC
Build the monitoring
platform that fits your needs
Search
Monitor
Share
Collaborate

CENTREDOC
SECURED
DocDB in your
private cloud
MIXED DATA
Mixe free data
with professional
ones
ARCHIVE
Private archive
with access rights
Search

CENTREDOC
Monitor
Visualise Automate
Automated alerts from
DocDB
Automated alerts from
commercial providers

CENTREDOC
Monitor
Visualise Automate Dashboard

CENTREDOC
ANALYSE
Multiple forms
for your experts
CONTRIBUTE
Add your own
information and
reports
CONTROL
Set access rights
for each user
Collaborate

CENTREDOC
SWISS CLOUD
Restrictive law
regarding fishing
discoveries
WORKFLOW
Create information
flow for a fluid
treatment
CUSTOMIZE
Give to each one
the right information
In the right form
Share

CENTREDOC
Search Monitor ShareCollaborate
Visit us at our booth !
Create the BI platform you need !

Contenu connexe

Tendances

Innovation means many different things to many people. Ask five people and you will likely get ten answers. But all agree that it is a key driver behind the success of organizations, the growth of economies and provides major contributions in addressing global problems. This presentation will examine various analytical methods and possible metrics for measuring innovation and determining relative performance of organizations. The challenges involved in assessing innovation and how these can be addressed will be explored. The pros and cons associated with the metrics identified will also be discussed with a view to identifying a practical method for assessing innovation.

II-SDV 2017: What is Innovation and how can we measure it?

Dr. Haxel Consult

IEEE is the world's largest technical membership association, with more than 420,000 members in over 160 countries. A Not-for-Profit organization, our mission is "Advancing Technology For Humanity." The IEEE Xplore Digital Library is the gateway to more than 30% of the world's current technical literature in electrical engineering, electronics, and computer science. Over 4.3 million full-text articles and papers Our subscribers include academic, corporate, and government organizations worldwide We publish the top-cited science and technology research in the field, most notably our journals, conferences, and standards According to a study from 1790 Analytics, IEEE literature is cited three times more often in US Patents than any other publisher and leads in European Patent citations. Patent referencing to IEEE literature has increased 896% since 1997. The importance of science and technical literature is rising and IEEE research is increasingly valuable to innovators. InnovationQ Plus, a powerful new patent discovery and analytics platform from the IEEE and IP.com, indexes IEEE full-text publications alongside one of the largest global patent literature databases in the industry. Content includes over 4 million documents from IEEE journals, conferences, and standards alongside a global database of over 100 million patents and patent applications. InnovationQ Plus also includes IP.com's proprietary Prior Art Database, Licensable Technology from universities and other non-patent literature including PubMed Central and the Internet Engineering Task Force (IETF).

IC-SDV 2018: IEEE

Dr. Haxel Consult

II-SDV 2017: Approaches of Web Information Analysis in a Day to Day Work Envi...

Dr. Haxel Consult

Adalimumab- comprehensive patent search

Kate Cleverley

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;

AI-SDV 2021 - Klaus Kater - The secret of successful CI: precise targeting + ...

Dr. Haxel Consult

New Product Introductions - BizInt

Dr. Haxel Consult

ICIC 2014 New Product Introduction ProQuest

Dr. Haxel Consult

Helix Brochure

Waseem Naik

2018 advanced data governance - slide share

Albert Hoitingh

Intelligent Classification Organizations continue to struggle with retaining information to meet regulatory and business requirements. As a result, many keep everything, sometimes longer than they should, increasing IT administrative overhead and business exposure and risk. To help address this challenge, Enterprise Vault supports Classification of all ingested content – email, files, Instant Messaging, Social Media and more. Customizable policies automatically determine what to classify and retain or discard and whether to tag an item for faster search, discovery or supervisory review. Intelligent Re-Classification What happens to your archive when your retention policies must evolve to be compliant with new regulations or business requirements? You adjust archive retention as needed. Reclassification helps ensure your archived information meets current regulations, retention and classification policies. You can revisit an Enterprise Vault archive with unlimited retention and use policies to define what information should be kept for business value, compliance or discovery and what should be deleted. You can even update retention periods on individual items.

Enterprise vault - Top 5 Enterprise Vault 12 Upgrade Must-Haves

dcVAST

Ultimate slideshare post

Rana Pratap Thakur

Lessons learned from the design of the SCIM API

Erik Wahlström

ICIC 2014 New Product Introduction Questel

Dr. Haxel Consult

Securing, storing and enabling safe access to data

Robin Rice

As data sets continue to grow, search remains a key technology for many applications. But what is the current state of the enterprise search market? Which providers are gaining market share, and what are the latest developments and innovations? Based on experience from dozens of recent search projects using a range of technologies, this presentation will summarize market conditions, discuss current best practices for creating great search systems, and suggest some future trends to watch out for.

The Enterprise Search Market in a Nutshell

Dr. Haxel Consult

Linear hub business plan

Sunghyuk Kim

SARoNGS project (Jens Jensen)

JISC.AM

Managing Your Research Data for Maximum Impact -Rob Daley 300616_Shared

Rob Daley

Une base de données graphes convient parfaitement aux cas d'utilisation de Master Data Management, tels que la création d'une vue à 360 degrés du client. Les entités du monde réel telles que les clients, les produits et les tickets de support, ainsi que les relations entre eux, peuvent être directement modélisées dans le graphe, ce qui permet l'analyse et la visualisation de l'ensemble de données combiné. Avant que cela ne se produise, les données doivent être collectées à partir d'un ensemble varié de sources et ingérées dans la base de données de graphes. Les données source peuvent être situées dans des fichiers plats, dans des bases de données relationnelles, dans des plates-formes basées sur le cloud ou même dans une file d'attente de messages. Extraire des données de leur source, les transformer en la structure et le format requis et les charger dans la base de données graphes (processus ETL) peut être un projet majeure. L’écriture de scripts personnalisés ou l’utilisation d’outils traditionnels ETL donne lieu à une solution fragile qui échoue face à la modification des structures de données et aux exigences, telles que l’acquisition de données en continu. Au cours de cette session, vous apprendrez à créer des pipelines de données robustes pour charger des données par lots et en continu dans Neo4j. Nous examinerons les particularités de différentes sources de données et examinerons des cas d'utilisation réels, tels que l'extraction de données clients du cloud et leur combinaison avec les données de produit d'une base de données relationnelle. Au préalable, nous ferons une courte introduction à Neo4j avec Cédric Fauvet, Business Développement France chez Neo4j.

Acquisition de données dans Neo4j pour le Master Data Management

Neo4j

HDIAC Information Sheet

Chuck Brooks

Tendances (20)

II-SDV 2017: What is Innovation and how can we measure it?

IC-SDV 2018: IEEE

II-SDV 2017: Approaches of Web Information Analysis in a Day to Day Work Envi...

Adalimumab- comprehensive patent search

AI-SDV 2021 - Klaus Kater - The secret of successful CI: precise targeting + ...

New Product Introductions - BizInt

ICIC 2014 New Product Introduction ProQuest

Helix Brochure

2018 advanced data governance - slide share

Enterprise vault - Top 5 Enterprise Vault 12 Upgrade Must-Haves

Ultimate slideshare post

Lessons learned from the design of the SCIM API

ICIC 2014 New Product Introduction Questel

Securing, storing and enabling safe access to data

The Enterprise Search Market in a Nutshell

Linear hub business plan

SARoNGS project (Jens Jensen)

Managing Your Research Data for Maximum Impact -Rob Daley 300616_Shared

Acquisition de données dans Neo4j pour le Master Data Management

HDIAC Information Sheet

En vedette

This paper revisits some of the issues discussed in our 2013 presentation "Challenges in Visualizing Pharmaceutical Business Information," where we analyzed some of the unique challenges in visualizing competitive intelligence information for the pharmaceutical industry. A key challenge for pharmaceutical companies is to evaluate the competitive landscape for drug launches many years in the future, based on a combination of publicly available drug pipeline and clinical trials data and internal company knowledge. This information is often conveyed in hand-drawn PowerPoint slides, which are very time consuming to create and update as the competitive landscape changes. In this paper we'll discuss approaches to developing a toolkit to facilitate the analysis and visualization of competitive drug launch timelines, and then show how to apply the same tools to a different problem -- forecasting the patent expiration landscape.

II-SDV 2016 Diane Webb - Challenges in Visualizing Pharmaceutical Information...

Dr. Haxel Consult

II-SDV 2016 Minesoft

Dr. Haxel Consult

The use of ontologies to aid in the development of text search queries, the quality and relevance ranking of results, and the categorization of patents has been well characterized. Similar work has been performed on non-patent scientific literature such as journal articles. We present here the employment of common life science ontologies to search both the entirety of the patent and non-patent literature corpora at the same time. The results of these searches can be readily studied in a single unified search result that allows for the annotation of key patent and non-patent documents in a mixed data-type environment.

II-SDV 2016 Denis Bayada - Concomitant Ontology-Driven Patent and Non-Patent ...

Dr. Haxel Consult

II-SDV 2016 Deep SEARCH 9

Dr. Haxel Consult

II-SDV 2016 VantagePoint

Dr. Haxel Consult

Information that is relevant for researchers and decision makers in the Life Sciences comes from many different backgrounds: Scientific publications, patents, news, clinical reports, user-generated content, they all may be required to understand trends, opportunities and threats. A key to providing quick and comprehensive overview is having information from various source in one place and semantically enrich and normalize them and relate them to one another. We present the key principles of a platform that serves that purpose and that provides users with insights into the scientific, clinical and competitive intelligence landscape of their respective area of interest. Forged in close collaboration with industry practitioners, the Luxid Biopharma Navigator is today used in production by hundreds of experts.

II-SDV 2016 Stefan Geißler Navigating complex information landscapes – Semant...

Dr. Haxel Consult

II-SDV 2016 GQ Life Sciences

Dr. Haxel Consult

II-SDV 2016 RightsDirect

Dr. Haxel Consult

SMEs represent a prime target for public authority awareness-raising policies especially as regards innovation and filing patents. Yet it is not always easy to get a handle on this population in terms of statistics, meaning that it is particularly difficult to systematically identify in the patent databases those SMEs that do file patent applications. Two census of SMEs conducted in 1999 and 2007, organised jointly by Bpifrance and INPI, allow the INPI to yearly identify SMEs among the companies that filed a patent application at the French patent office. This study reveals the importance of SMEs among the total patent applicant population. They show that in France, in 2014, SMEs represented 67% of the French corporate bodies that filed patent applications, but only accounted for 23% of the patent applications published in 2014. This share of SMEs and large companies in the patent applications of French corporate bodies are stable since 2011. The figures highlight the fact that in 2014, on average, an SME filed 1.4 patents, compared to 15.2 for a large company (more than 5,000 employees). We observe regional disparities: regions such as Alsace, Languedoc-Roussillon, Pays de la Loire and Poitou-Charentes are characterised by the highest share of patent application from SMEs. And SMEs are more specialised in medical technologies.

II-SDV Emmanuelle Fortune - SMEs as Patent Applicants in France in 2014

Dr. Haxel Consult

Boehringer Ingelheim has been developing dedicated Life Science SEARCHCORPORA for startups, scientific literature and news tracking based on the Web Data Analysis platform Deep SEARCH 9. Using the Deep SEARCH 9 approach, Boehringer Ingelheim is capable of tapping directly any web resources like online websites data bases, web sites or news feeds. Use case 1: SEARCHCORPUS® for life science startups: We find startup information we could not find in public search engines. Use case 2: Life science news SEARCHCORPUS®: 100s of incoming mails and alerts are processed every day and websites and articles behind the news tags are crawled automatically. The purpose of these applications is that Scientists can subscribe to the services to have compilations of results of personalized deep searches sent to them automatically or that they can alternatively use faceted search on the life science SEARCHCORPORA interactively.

II-SDV 2016 Aleksandar Kapisoda, Klaus Kater - Deep Web Search

Dr. Haxel Consult

II-SDV 2016 GRIDLOGICS

Dr. Haxel Consult

One of the key elements in understanding a technology sector or a competitor’s activities is to measure and detect any significant changes over time that may indicate a declining interest or a new hot emerging area. But how do we spot the signal from the noise? What constitutes a significant change? This depends on how we measure change which in turn depends on the measure of time we use. In scientific literature, we have limited choice – publication date (but even that is changing with wide availability of electronic pre-prints). In patent literature, publication date provides a measure of when an invention is publicly disclosed, but priority date is perhaps a truer measure of when the invention was made. And is it better to look at individual dates, or use moving windows of time? This presentation will consider these questions using a case study approach to determine the impacts and effectiveness of the different approaches.

II-SDV 2016 Bob Stembridge We have all the Time in the World; a Review of ho...

Dr. Haxel Consult

II-SDV 2016 Linguamatics

Dr. Haxel Consult

This joint presentation will focus on a project between CENTREDOC and the ARMASUISSE Science and Technology Foresight program to set up an optimized Patent Landscape process. The talk will outline the major bottlenecks identified in the existing process, the solutions considered and implemented by CENTREDOC, as well as the results achieved by ARMASUISSE in its capacity to anticipate and get the necessary understanding of emerging technologies. As technologies can be considered independently of the domain of application, creating a contributory platform providing structured information about technologies is of common general interest at governmental and industrial level, both national and international.

II-SDV 2016 Raphael Ilmer, Quentin Ladetto - Optimization of Patent Landscape...

Dr. Haxel Consult

II-SDV 2016 BizInt

Dr. Haxel Consult

This presentation will give some guidelines on how to create a meaningful Patent Landscapes. Generating patent landscaping reports seems simple, but it isn’t. For making patent landscapes you have to take several different issues into consideration. It’s important at the start to already have in mind what kind of landscape report you are going to prepare, and choose a topic of interest, but preferable not one that is too broad. It’s also extremely important to have a clean (80-90% relevance) dataset that the landscape is based on; otherwise the outcome will be rubbish. And of course, do not use landscapes for questions that require a legal opinion (like Freedom-to-operate conclusions!!). Patent landscapes are not aimed to be as precise as other patent searches. Some more important issues has to be taken in account and are presented.

II-SDV 2016 Aalt van de Kuilen - The Art of Patent Landscaping

Dr. Haxel Consult

II-SDV 2015, 20 - 21 April, in Nice

Dr. Haxel Consult

he II-SDV meeting takes place in Nice in April 2016 for an intensive two days. Venue is the Hotel Plaza in central Nice. The meeting provides an international forum for those in the field of advanced search applications, data and text mining, and visualization technology. The primary focus is on tools for intelligence and the meeting examines the requirements of specialists in scientific and technical information. The meeting will be of interest to those who wish to update themselves and keep in touch with the leading edge of information search and analysis technologies; it features approximately 22 speakers for the two days. There will be an adjacent, focused exhibition to complement the conference programme.

II-SDV 2015 The International Information Conference on Search, Data Mining a...

Dr. Haxel Consult

The 2017 II-SDV Conference in Nice, 24 - 25 April 2017 The II-SDV meeting takes place in Nice in April 2017 for an intensive two days. Venue is the Hotel Plaza in central Nice. The meeting provides an international forum for those in the field of advanced search applications, data and text mining, and visualization technology. The primary focus is on tools for intelligence and the meeting examines the requirements of specialists in scientific and technical information. The meeting will be of interest to those who wish to update themselves and keep in touch with the leading edge of information search and analysis technologies; it features approximately 22 speakers for the two days. There will be an adjacent, focused exhibition to complement the conference programme.

II-SDV 2017 in Nice - The International Information Conference on Search, Dat...

Dr. Haxel Consult

En vedette (19)

II-SDV 2016 Diane Webb - Challenges in Visualizing Pharmaceutical Information...

II-SDV 2016 Minesoft

II-SDV 2016 Denis Bayada - Concomitant Ontology-Driven Patent and Non-Patent ...

II-SDV 2016 Deep SEARCH 9

II-SDV 2016 VantagePoint

II-SDV 2016 Stefan Geißler Navigating complex information landscapes – Semant...

II-SDV 2016 GQ Life Sciences

II-SDV 2016 RightsDirect

II-SDV Emmanuelle Fortune - SMEs as Patent Applicants in France in 2014

II-SDV 2016 Aleksandar Kapisoda, Klaus Kater - Deep Web Search

II-SDV 2016 GRIDLOGICS

II-SDV 2016 Bob Stembridge We have all the Time in the World; a Review of ho...

II-SDV 2016 Linguamatics

II-SDV 2016 Raphael Ilmer, Quentin Ladetto - Optimization of Patent Landscape...

II-SDV 2016 BizInt

II-SDV 2016 Aalt van de Kuilen - The Art of Patent Landscaping

II-SDV 2015, 20 - 21 April, in Nice

II-SDV 2015 The International Information Conference on Search, Data Mining a...

II-SDV 2017 in Nice - The International Information Conference on Search, Dat...

Similaire à II-SDV 2016 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.

II-SDV 2017: Centredoc

Dr. Haxel Consult

AI-SDV 2022: New Product Introductions: CENTREDOC

Dr. Haxel Consult

AI-SDV 2021 - Harald Jenny - Integrated Artificiel Intelligence – A Factory P...

Dr. Haxel Consult

Enterprise Search Case Study: Swedish Armed Forces

Findwise

EOSC Digital Innovation Hub (EOSC DIH)

EOSC-hub project

Corporate Presentation EN [Autosaved]

Steve Hayward

Quality control, the PRESTO way PRESTO Audit Manager is strongly recommended to businesses looking to embed a proactive quality control discipline into the DNA of their organisation transforming internal audit management from an administrative burden into a competitive advantage With PRESTO’s newest setup features and out-of-the-box reporting recently released in production together with a team of Swiss French engineers, 30 minutes is all you need to setup your company and start managing quality, the PRESTO way.

PRESTO Audit Manager

TOPP Tactical Intelligence Ltd

Extelligence sro

Khalid Pervez

IT.integro is the leading Microsoft Dynamics NAV partner in Poland. IT.integro is a team of professionals who are passionate about their work and create the company’s success. Owing to their knowledge and involvement, IT.integro has become a synonym for professionalism and reliability. Presently, we employ: 80 employees, 60 consultants, 9 consultant teams, 8 Help Desk consultants,4 technical consultants. We work to ensure the success of your company!

IT.integro. Company presentation

IT.integro Sp. z o.o.

Dear Reader, After Dave Brown’s much appreciated ‘Hitchhikers guide to the Swiss French Tech Startup Community’ last updated in Jan 2015, it was time for another update. Inno-Fuel’s team tried to pull most of the latest relevant info together which we hope you will appreciate. A special thanks to Eric Maire, Colin Turner and Jérôme Vasamillet for their great contribution ! We hope you appreciate the update and please inform us of any comments or relevant continuous updates you might have regarding the ecosystem !

Inno-Fuel overview of western Switzerland's startup ecosystem (2017)

Alexandre Grutman

Enterprise Search Case Study: Wolters Kluwer Scandinavia

Findwise

Coney dn aslidespack

drs Pieter de Kok RA

PRESTO Audit Manager is strongly recommended to businesses looking to embed a proactive quality control discipline into the DNA of their organisation transforming internal audit management from an administrative burden into a competitive advantage With PRESTO’s newest setup features and out-of-the-box reporting recently released in production together with a team of Swiss French engineers, 30 minutes is all you need to setup your company and start managing quality, the PRESTO way.

PRESTO Audit Manager

TOPP Tactical Intelligence Ltd

Dansk ORCID seminar 2: Projekt status og nyt om orcid

Mikael Elbæk

Tallium demo Jan 18

AquaSPE AG

CompanyPresentation_EN

Uwe Gerlinger

Is it sensible to use Data Vault at all? Conclusions from a project.

Capgemini

Fraunhofer and SINTEF jointed Industrial Data Space Association in early 2016. Industrial Data Space stands for safer data exchange between companies where the producer of data remains the owner of the data and maintains sovereignty over the use of that data. IDS Association aims to define the conditions and governance for a reference architecture and interfaces aiming at international standards. This standard is actively developed and updated on the basis of use cases. It forms the basis for a number of certified software solutions and business models, the development of which is fostered by the association. Thorsten Huelsmann and Ernst H. Kristiansen talked on this topic during the German-Norwegian Dialogue on Bilateral and European Cooperation , September 29 2016 at Berlin.

Fraunhofer – SINTEF: towards an initiative on Data Sovereignty in Europe

Thorsten Huelsmann

Embracing Cloud Deployment for Big Data and Dev Ops

Nick Brown

Embracing Cloud Deployment for Big Data and DevOps

Steve Woodward

Similaire à II-SDV 2016 Centredoc (20)

II-SDV 2017: Centredoc

AI-SDV 2022: New Product Introductions: CENTREDOC

AI-SDV 2021 - Harald Jenny - Integrated Artificiel Intelligence – A Factory P...

Enterprise Search Case Study: Swedish Armed Forces

EOSC Digital Innovation Hub (EOSC DIH)

Corporate Presentation EN [Autosaved]

PRESTO Audit Manager

Extelligence sro

IT.integro. Company presentation

Inno-Fuel overview of western Switzerland's startup ecosystem (2017)

Enterprise Search Case Study: Wolters Kluwer Scandinavia

Coney dn aslidespack

PRESTO Audit Manager

Dansk ORCID seminar 2: Projekt status og nyt om orcid

Tallium demo Jan 18

CompanyPresentation_EN

Is it sensible to use Data Vault at all? Conclusions from a project.

Fraunhofer – SINTEF: towards an initiative on Data Sovereignty in Europe

Embracing Cloud Deployment for Big Data and Dev Ops

Embracing Cloud Deployment for Big Data and DevOps

Plus de Dr. Haxel Consult

AI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management

Dr. Haxel Consult

Knowledge Graphs are an increasingly relevant approach to store detailed knowledge in many domains. Recent advances in NLP allow to enrich Knowledge Graphs through automated analysis of large volumes of literature, reducing a lot the efforts in traditional manual information capturing. In our presentation we report the approach taken in a project with partner Fraunhofer SCAI in the life sciences where a knowledge graph organising detailed facts about psychiatric diseases has been computed. Information of cause-effect relations between proteins, genes, drugs and diseases has been encoded in the BEL (Biological Expression Language) and imported into a Graph database to approach an indication-wide Knowledge Graph for the selected therapeutic area. Ultimately, updating the graph will amount to just rerunning the analysis on the newly published literature.

AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...

Dr. Haxel Consult

In 2019 the UK was the first major economy to embrace a legal obligation to achieve net zero carbon emissions by 2050. More broadly, the 2021 UK Innovation Strategy sets out the UK government’s vision to make the UK a global hub for innovation by 2035 with a target of increasing public and private sector R&D expenditure to 2.4% of GDP to support the UK being a science superpower with a world-class research and innovation system. IP rights create an incentive for R&D which ultimately leads to innovation. Analysis and insights from IP data can therefore help provide a better understanding of how the IP system is being used and where and what innovation is taking place. Research and analysis of IP data is a key input to the ongoing work of the UKIPO’s Green Tech Working Group which seeks to: further the UK’s status as a global leader by making the UK’s IP environment the best for innovating green technology; develop and deliver IP policies to support government’s ambition on climate change and green technologies; and to help innovators best protect and commercialise their green tech innovations both at home and internationally. The UKIPO has been developing a broad portfolio of ‘green’ IP analytics research. A series of patent analytics reports have been published looking at green technologies, and analysis of how the UK’s Green Channel scheme for accelerated processing of green patent applications has been conducted. Patents have been used to identify technological comparative advantage within different green technologies at a country level, and new insights uncovered by mapping green technology patents to the UN Sustainable Development Goals (SDGs). Trade mark data provides a timeliness and closeness to market factor that patent data does not, and complementary trade mark analysis of UK ‘green’ trade marks, identified using a machine learning algorithm, provides a commercialisation angle to our research.

AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...

Dr. Haxel Consult

Word embeddings, deep learning, transformer models and other pre-trained neural language models (sometimes recently referred to as "foundational models") have fundamentally changed the way state-of-the-art systems for natural language processing and information access are built today. The "Data-to-Value" process methodology (Leidner 2013; Leidner 2022a,b) has been devised to embody best practices for the construction of natural language engineering solutions; it can assist practitioners and has also been used to transfer industrial insights into the university classroom. This talk recaps how the methodology supports engineers in building systems more consistently and then outlines the changes in the methodology to adapt it to the deep learning age. The cost and energy implications will also be discussed.

AI-SDV 2022: Accommodating the Deep Learning Revolution by a Development Proc...

Dr. Haxel Consult

In the patent domain, all types of issues, from very specific search requirements to the linguistic characteristics of the text domain, are accentuated. Consequently, to develop patent text mining tools for scientists and patent experts, we need to understand their daily work tasks, as well as the linguistic character of the text genre (i.e., patentese). Patent text is a mixture of legal and domain-specific terms. In processing technical English texts, a multi-word unit method is often deployed as a word-formation strategy to expand the working vocabulary, i.e., introducing a new concept without the invention of an entirely new word. This productive word formation is a well-known challenge for traditional natural language processing tools utilizing supervised machine learning algorithms due to limited domain-specific training data. Deep learning technologies have been introduced to overcome the reduction in performance of traditional NLP tools. In the Artificial Researcher technologies, we have integrated explicit and implicit linguistic knowledge into the deep learning algorithms, essential for domain-specific text mining tools. In this talk, we will present a step-by-step process of how we have developed the mentioned text mining tools. For the final outline, we will also demonstrate how these tools can be integrated in a cross-genre passage retrieval system, based on a technology from 2016 that still holds the state-of-the-art within the patent text mining research community in 2022.

AI-SDV 2022: Domain Knowledge makes Artificial Intelligence Smart Linda Ander...

Dr. Haxel Consult

In 2013 we witnessed an evolutionary change in the NLP field evolved thanks to the introduction of space embeddings that, with the use of deep learning architectures, achieved human-level performances in many NLP tasks. With the introduction of the Attention mechanism in 2017 the results were further improved and, as result, embeddings are quickly becoming the de facto standards in solving many NLP problems. In this presentation, you will learn how generate and use space embedding for search purposes and provide comparison metrics to more traditional relevance-based search engines. Moreover, I will provide some initial results on a paper currently under review that provides an insight on hyperparameter tuning during the generation of embeddings.

AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...

Dr. Haxel Consult

AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...

Dr. Haxel Consult

AI-SDV 2022: Machine learning based patent categorization: A success story in...

Dr. Haxel Consult

AI-SDV 2022: Machine learning based patent categorization: A success story in...

Dr. Haxel Consult

It is relatively easy for a human to read a document and quickly figure out which concepts are important. However, this task is a difficult challenge for a machine. During the past few decades, there have been two main approaches for concept identification: Natural Language Processing and Machine Learning. During the early part of this century, Machine Learning made great strides as new techniques came into wider use (SVM’s, Topic Modeling, etc..). Sensing the competition, Natural Language Processing responded with deployment of new emerging techniques (sematic networks, finite state automata, etc..). Neither approach has completely solved the WHAT problem. Advances in Artificial Intelligence have the potential to significantly improve the situation. Where AI is making the most impact is as an enhancement to make Machine Learning and Natural Language Processing work better and, more importantly, work together. This presentation looks at some of this history and what might happen in the future when we blend the interpretation of language with pattern prediction.

AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...

Dr. Haxel Consult

Trademarks serve as key leading indicators for innovation and economic growth. As the vanguards of new and expanding enterprises, trademarks can be used to study entrepreneurship and shifting market demands in response to varying economic factors. This responsiveness has been seen as recently as the COVID-19 pandemic, where trademark research revealed key insights about business reaction to the global upheaval. At CIPO, we have been delving more deeply than ever before into trademark analysis by leveraging cutting-edge natural language processing (NLP) tools to derive actionable business intelligence from trademark data. In this presentation, we present a survey of NLP in use at CIPO and the insights we have learned applying them. These insights include COVID-19 responses, line-of-business trends based on firm characteristics, and more. We also discuss ongoing and future trademark research projects at CIPO. These projects include emerging technology detection methods and high-resolution trademark classification systems. We conclude that artificial intelligence-enhanced tools like NLP are key components of future exploitation of trademark data for business and economic intelligence.

AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...

Dr. Haxel Consult

In our customer projects involving automated document processing, we often encounter document types providing crucial data in the form of tables. While established text analytics algorithms are usually optimized to operate on running text, they tend to produce rather poor results on tables as they do not capture the non-sequential relations inside them (e.g. interpret the content of a table cell relative to its column title, interpret line breaks inside a cell differently from line breaks between cells or rows). While there are elaborate information extraction products in the market for a few highly specific types of tabular documents, there is no general approach out there. The main cause for this is the fact that table structures can be encoded by a heterogenous range of layout means (e.g. column boundaries can be signaled by lines vs. aligned text vs. white space). In this talk, we will illustrate several solutions that we have developed for a range of challenges occurring in this context, both for scanned and digitally generated documents.

AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...

Dr. Haxel Consult

Most scientific journals request, that the complete set of research data is published simultaneously with the peer-reviewed paper. The publication of the research data usually is carried out as so-called "Supplementary Material", attached to the original paper, or on a "Research Data Repository". Both forms have in common, that the data is published usually unstructured and not in an uniform machine processable format. This makes its further use in electronic tools for AI or data mining unnecessarily difficult or even impossible. A concept is presented, in which the data is digitally recorded, following the principle of FAIR data, as part of the publication process. This digital capture makes the data available to the scientific community for easy use in data mining and AI tools. The data in the repository contains links to the publication to document its origin. The concept is applicable for preprints, peer-review papers, diploma and doctoral theses and is particularly suitable for open access publications. Moreover, the presentation highlights correspondent activities, which were released in scientific publications recently.

AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...

Dr. Haxel Consult

AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...

Dr. Haxel Consult

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: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...

Dr. Haxel Consult

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: Copyright Clearance Center

Dr. Haxel Consult

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: Lighthouse IP

Dr. Haxel Consult

AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...

Dr. Haxel Consult

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!

AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...

Dr. Haxel Consult

AI-SDV 2022 The Meeting AI-SDV 2022 Conference and Exhibition is planned to be held physically and virtually. Speakers, attendees and exhibitors are invited to join physically and virtually in Vienna, Austria. We are developing a range of digital formats that respond precisely to the speakers, attendees and exhibitors needs, enabling individuals and exhibitors from AI industry and related sectors worldwide to participate in the AI-SDV 2022 in Vienna. The Artificial Intelligence Conference on Search, Data and Text Mining, Analytics and Visualization. The 2022 AI-SDV Conference in Vienna, Austria, 10th - 11th October 2022. AI-SDV 2022 is the place to be for everyone involved in advanced search and data applications, text mining and visualization technologies. Individuals and companies that are shaping the future of this exciting space that surrounds us and impacts us all will present their latest research findings, tech developments and visions for the future. Enjoy a full-on two days of learning, networking and exploring technologies and concepts that are state of the art and will continue to change way we as individuals and organisations work, rest and play. The focus is on Artificial Intelligence (AI), Digitization 2.0 (about making companies, processes and people ready for AI), Deep Learning and other topics identified by our community, who are specialists working in scientific and technical information. The event features approximately 22 speakers over two days, plus an exhibition to complementing the conference programme. As past attendees tell us, Vienna is a fabulous location and beyond the formal meetings taking place in the conference and exhibition space, we make the most of this gorgeous location for informal evening receptions and networking dinners.

The Artificial Intelligence Conference on Search, Data and Text Mining, Analy...

Dr. Haxel Consult

Plus de Dr. Haxel Consult (20)