ICIC 2017: New product presentationsLighthouse IP

•

1 recomendación•1,018 vistas

Dr. Haxel Consult

Internet

Lighthouse IP
ICIC 2017, Heidelberg
Update on Lighthouse IP
Willem Geert Lagemaat

CONTENT
– Patent coverage update
– IP Data and Business Information
- Cooperation with Dun and Bradstreet
- DIAMOND: Global Bibliographic and Legel IP database

PATENT COVERAGE UPDATE
Expanding patent full text coverage
– 70 authorities in full text and MT new additions include
a.o:
• Mongolia
• Ukraine
• Iran
• Belarus
– 140 countries bibliographic data (not just DOCDB)
– Sourcing gazettes directly from 80+ authorities
– Expanding legal status to 100+ authorities
– Access provided via partners (please visit our booth for
more information)

IP AND BUSINESS INFORMATION
Growing interest from various sides of industry to have
insight into IP holdings
For finance departments patents are often a black box
Representing an increasingly growing part of the
business
Who owns what?

COOPERATION WITH DUN AND BRADSTREET
(D&B)
Dun and Bradstreet is the worlds largest business
information provider
Over 90% of fortune 500 companies use D&B data
Introduction to the DUNS®
• Unique number per company (entity)
• Assigned by D&B
• Required by various government bodies in US
Corporate tree (ownership, structure, holdings)

DIAMOND Global Bibliographic and Legal IP Data
Data sources today: DOCDB and INPADOC
• analyzing gaps in DOCDB
• completeness of countries and years
• Latency/topicality/frequency of update
• analyzing gaps in INPADOC
• 57 countries, 25 up-to-date

DIAMOND Global Bibliographic and Legal IP Data
Diamond 4 stages:
• 1. Diamond Bibliographic PRS : DOCDB-EPO 106 countries; 47 up-dated by
LHIP.
• 2. Diamond Bibliographic Global : DOCDB + data of all available countries,
currently 156 countries
• 3. Diamond Legal Status PFS : INPADOC-EPO + enhanced by LHIP (up-to-
date from gazettes)
• 4. Diamond Legal Status Global : INPADOC + data of all available countries

Data Content and Form
Analyzing the biblio and legal content of the gazettes,
applications, grants, utility models, designs
• Bibliographic data:
WIPO ST.9
INIDs
• Legal data:
• WIPO ST.17
RECOMMENDATION FOR THE CODING OF HEADINGS OF
ANNOUNCEMENTS MADE IN OFFICIAL GAZETTES (1990)
• WIPO ST.27
• Legal Status Standardisation (June 2017)

QUESTIONS?
Thanks for your attention
Please visit our booth

Más contenido relacionado

La actualidad más candente

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

Dr. Haxel Consult

Dieter Küry (Novartis Pharma, Switzerland) Using analytical methods are more and more replacing database searching in a knowledge manager's daily activities. In this presentation various facets of publication analysis will be presented and discussed. These new methods were applied for the analysis of publications in scientific journals and visuals were created to deduct publications strategies. On the technical side, the overall analysis process requires diverse tools for reference managing, text analysis and visualization. The impact on skills of the knowledge manager who moves from the expert for query languages to the expert for creation and maintaining of thesauri is also shown. Main benefit of the analytical methods compared to traditional database searching is the manifold use of results, which are easily adaptable to new requirements.

ICIC 2017: Publication Analysis and Publication Strategy

Dr. Haxel Consult

CIC is the International Conference on Trends for Scientific Information Professionals. 29th ICIC International Conference for the Information Community For those in the sci-tech world, sharing best practices, networking and evaluating trends have become matters of considerable importance, and the annual ICIC Meeting & Exhibition is the significant forum for this, attracting over 100 attendees from the main sci-tech companies and information, service or software providers. It will be a venue where attendees will learn about new ways to work with disseminate scientific and patent information. Started in 1989 ... These exciting and highly respected annual conferences, that started in Montreux in 1989 and were subsequently held in Annecy, Nîmes, Barcelona, Nice, Vienna and Berlin have always provided a barometer as to the strengths and frailties of the world of sci-tech and patent information. The conference lasts for two days and features approximately 24 formal presentations, panels on topical matters, all interspersed with short new product information presentations. All sessions are plenary. The conference normally begins with a reception and Welcome Dinner on the first evening to enable attendees to begin to network with each other. Lunches are taken at the conference venue, and breaks are designed to facilitate networking and interaction. A focused exhibition of approximately 20 stands is integrated within the conference. Attendance at these meetings is highly international, with no one nationality predominating. The 2017 ICIC conference is organised by Dr Haxel Congress and Event Management. Subject Areas for the 2017 Programme The traditional focus of the ICIC programmes is subjects of interest to information professionals in a scientific or technical environment. As in previous years, this year's programme contains a number of presentations examining aspects of patent information retrieval, including drug discovery; patent information presents many challenges and is thus an excellent test-bed when it comes to information technology. The ICIC meeting's roots in chemical information also ensure that that area features prominently; chemical information was one of the first fields to attract modern information technologies back at the end of the twentieth century and the very beginning of the twentyfirst. Next ICIC: 23 - 24 October 2017, Heidelberg, Germany. Location: Heidelberg Congress House http://www.heidelberg-conventions.com/ Neckarstaden 24, 69117 Heidelberg

29th ICIC International Conference for the Information Community

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.

ICIC 2017: Technology Scouting: Decision Support in Strategic Analyses for Te...

Dr. Haxel Consult

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

Dr. Haxel Consult

II-PIC 2017: Product presentation Lighthouse IP

Dr. Haxel Consult

WIPO started work in the area of patent analytics in 2010 with a Development Agenda project on “Developing Tools for Access to Patent Information” which resulted in the production of a series of Patent Landscape Reports (WIPO’s patent landscape reports can be found here). These reports, prepared in cooperation with various UN Agencies, non-governmental organizations, research institutes and national IP Offices, analyze patent activity in various topics in the areas of public health, food and agriculture, environment and energy, and disabilities. The key findings are often summarized in an infographic. In 2013 WIPO started working also on awareness raising and capacity building in the area of patent analytics. Apart from various workshops organized on this topic, WIPO published in September 2015 the “Guidelines for Preparing Patent Landscape Reports”. The Guidelines describe the objectives and motivations for preparing Patent Landscape Reports (PLR) and other types of patent analysis, the tasks associated with patent analytics, as well as the stages in the preparation of PLRs, providing also some insights from WIPO’s experience in the area. Since 2015 WIPO is exploring open source tools for patent analytics purposes in the framework of the preparation of a Manual on Open Source Tools for Patent Analytics. Open source tools are typically used by other disciplines, usually business/data analysts, statisticians, IT professionals and scientists, rather than with regard to patent data. Nevertheless, in recent years they started emerging as an alternative and/or a complement to ready-to-use tools, providing flexibility and adaptability in different analysis types. In view of the necessary programming related to this type of tools, WIPO developed step-by-step instructions in the Manual with example datasets, and will provide capacity building activities with training on patent analytics for Technology and Innovation Technology Support Centers (TISCs) around the world (for more information on the TISC program please visit www.wipo.int/tisc) .

II-SDV 2016 Irene Kitsara - Patent Landscape Reports and Other WIPO Activitie...

Dr. Haxel Consult

Feinäugle Roland (European Patent Office, Austria) A recent study commissioned by the EPO on the involvement of (patent) information in the innovation process in industry underlines the role of patent information in the various innovation stages. This result gives further impetus to the EPO's patent information strategy, aimed at supporting the economy by providing the access to a wealth of patent-related information, be it from its own patent granting process or its collection of worldwide bibliographic, legal status, procedural and full-text data. In the presentation we highlight some key findings of the study and give an overview of the EPO’s patent information products and services. We will discuss how they can be used for technology-specific searches, for getting insight into the legal and procedural status of an application during and after its grant procedure, and for the statistical analysis of bulk data for business intelligence purposes. The talk covers the EPO’s free-of-charge Espacenet as well as our flagship product PATSTAT, both with a worldwide coverage. It also highlights the ever-improving European Patent Register and its accompanying services as well as our RESTful Open Patent Services.

II-PIC 2017: Gain insight into technical, legal and business information thro...

Dr. Haxel Consult

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

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

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

ICIC 2017: New Poduct presentations InfoChem

Dr. Haxel Consult

II-SDV 2017: Gridlogics Technologies

Dr. Haxel Consult

II-SDV 2016 Minesoft

Dr. Haxel Consult

II-PIC 2017: Porduct presentation minesoft

Dr. Haxel Consult

II-PIC 2017: Product Presentation Gridlogics

Dr. Haxel Consult

Gouraj Yadav (Hourglass Research, India) With growing competition and the constant fear of being struck by disruption, it’s becoming increasingly tougher for corporate R&D departments to strategize research vis-à-vis stringent budgets. Avoiding re-inventing the wheel further poses to be an on-going challenge. In-house IP teams today largely adopt a reactive approach in which they tap ideas and inventions resulting from R&D and pursue patent protection. It would be beneficial if IP teams provide a proactive assistance to R&D teams and assist them in channeling R&D in the right direction. The presentation discusses how in-house IP teams can build an organized patent information database for R&D teams and guide them. The database can act as a common platform for which the R&D folks can have easy access to get the required technical information. Inventors can benefit from the insights received through such an organized database and can better understand the existing state-of-the-art. The presentation further discusses ways in which the database can be exploited for taking strategic R&D decisions.

II-PIC 2017: Optimizing R&D strategy through organized patent database

Dr. Haxel Consult

A journey in the Dark Web, for companies looking to take control of their search strategy. Objective if this presentation is to prove that any reasonable cost, any organisation can setup its own search strategy, outside or in parallel of its document management strategy. Challenge at French Ministry is to aggregate internal content, external content on social network (pinterest, youtube, facebook) and external legacy WebSite content (other Website from agency in relation with Ministry) and provide a brand new Web Site with "best of the bread" interface : search engine, auto completion and word correction, easy custom and secured navigation Result is awesome, for a budget kept under control, we provided a new Drupal Module to monitor and configure Solr6 indexation and search engine, together with custom API to index external WebSite. This session will come with a presentation of the Project Architecture (multi tiers servers) and a live demo of the Search interface

II-SDV 2017: Custom Open Source Search Engine with Drupal 8 and Solr at Frenc...

Dr. Haxel Consult

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

Dr. Haxel Consult

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

Dr. Haxel Consult

La actualidad más candente (20)

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

ICIC 2017: Publication Analysis and Publication Strategy

29th ICIC International Conference for the Information Community

ICIC 2017: Technology Scouting: Decision Support in Strategic Analyses for Te...

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

II-PIC 2017: Product presentation Lighthouse IP

II-SDV 2016 Irene Kitsara - Patent Landscape Reports and Other WIPO Activitie...

II-PIC 2017: Gain insight into technical, legal and business information thro...

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

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

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

ICIC 2017: New Poduct presentations InfoChem

II-SDV 2017: Gridlogics Technologies

II-SDV 2016 Minesoft

II-PIC 2017: Porduct presentation minesoft

II-PIC 2017: Product Presentation Gridlogics

II-PIC 2017: Optimizing R&D strategy through organized patent database

II-SDV 2017: Custom Open Source Search Engine with Drupal 8 and Solr at Frenc...

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

Destacado

Srinivasan Parthiban (VINGYANI, India) Deep learning is hot, making waves, delivering results, and is somewhat of a buzzword today. There is a desire to apply deep learning to anything that is digital. Unlike the brain, these artificial neural networks have a very strict predefined structure. The brain is made up of neurons that talk to each other via electrical and chemical signals. We do not differentiate between these two types of signals in artificial neural networks. They are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Another buzzword that was used for the last few years across all industries is “big data”. In biomedical and health sciences, both unstructured and structured information constitute "big data". On the one hand deep learning needs lot of data whereas “big data" has value only when it generates actionable insight. Given this, these two areas are destined to be married. The couple is made for each other. The time is ripe now for a synergistic association that will benefit the pharmaceutical companies. It may be only a short time before we have vice presidents of machine learning or deep learning in pharmaceutical and biotechnology companies. This presentation will review the prominent deep learning methods and discuss these techniques for their usefulness in biomedical and health informatics.

ICIC 2017: The Next Era: Deep Learning for Biomedical Research

Dr. Haxel Consult

Willem-Geert Lagemaat (Lighthouse IP Group, The Netherlands) A presentation on the development of AI in the IP field. Will patents in future be (partly) drafted by the computer? And how about retrieving knowledge from patents using AI? Will we be able to find sweet spots in technology by technology? This presentation wants to deepen the discussion on this topic and our thoughts on how open we are for these developments.

ICIC 2017:

Dr. Haxel Consult

Fernando Huerta (RISE Bioscience & Materials, SE) Alexander Minidis (Collaborative Drug Discovery - CDD VAULT, Sweden) How much information does the scientists need to design new potential drugs? A thorough overview of public scientific information sources (open access) and methods to collect, process, analyse and visualize this information will be presented. A direct application of such free available information in conjunction with freeware will be described in relation with the efforts of the scientific community to find effective medicines for the ZIKA virus.

ICIC 2017: Freeware and public databases: Towards a Wiki Drug Discovery?

Dr. Haxel Consult

ICIC 2017: New product presentations CAS

Dr. Haxel Consult

Alexander Giesen (Varidian, Germany) Patent families may introduce an additional layer of complexity to many patent searches. FTO searches and portfolio analyses are in particular affected by patent families. The presentation discusses issues caused by patent families and looks at different approached for dealing with them: approaches to patent family search by various search engines, selection of the best family member based on the scope of the search, selection considering the language skills of the patent researcher, dealing with complex families, family legal status and reporting. The selection of patent family members for FTO searches and patent statistics will be demonstrated in a brief case study.

ICIC 2017: Dealing with Patent Families in FTO Searches, Portfolio Analysis a...

Dr. Haxel Consult

ICIC 2017: New Poduct presentations CFL Software

Dr. Haxel Consult

ICIC 2017: New Product Introduction info apps

Dr. Haxel Consult

ICIC 2017: New product presentation EXPERT SYSTEM

Dr. Haxel Consult

Christopher Southan (The IUPHAR/BPS Guide to PHARMACOLOGY, UK) As of August 2017, the major automated patent chemistry extractions (in ascending size, NextMove, SCRIPDB, IBM and SureChEMBL) are included submitters for 21.5 million CIDs from the PubChem total of 93.8. The following aspects will be expanded in this presentation, starting with advantages; a) while the relative coverage between open and commercial sources is difficult to determine (PMID 26457120) it is clear that the majority of patent-exemplified structures of medicinal chemistry interest (i.e. from C07 plus A61) are now in PubChem b) this allows most first-filings of lead series and clinical candidates to be tracked d) the PubChem tool box has query, analysis, clustering and linking features difficult to match in commercial sources, e) many structures can be associated with bioactivity data f) connections between manually curated papers and patents can be made via the 0.48 million CID intersects with ChEMBL. However, looking more closely also indicates disadvantages; a) extraction coverage is compromised by dense image tables and poor OCR quality of WO documents, b) SureChEMBL is the only major open pipeline continuously running in situ but has a PubChem updating lag, c) automated extraction generates structural “noise” that degrades chemistry quality d) PubChem patent document metadata indexing is patchy (although better for SureChEMBL in situ) d) nothing in the records indicateas IP status, e) continual re-extraction of common chemistry results in over-mapping (e.g. 126,949 patents for aspirin and 14,294 for atorvastatin), f) authentic compounds are contaminated with spurious mixtures and never-made virtuals, including 1000s of deuterated drugs g) linking between assay data and targets is still a manual exercise. However, all things considered the PubChem patent “big bang” presents users with the best of both worlds (PMID 26194581). Academics or smaller enterprises who cannot afford commercial solutions can now patent mine extensively. For those who have such subscriptions, PubChem has become an essential adjunct/complementary source for the analysis of patent chemistry and associated bio entities such as diseases and drug targets.

ICIC 2017: Looking at the gift horse: pros and cons of over 20 million patent...

Dr. Haxel Consult

ICIC 2017: New Poduct presentations BizInt

Dr. Haxel Consult

Destacado (10)

ICIC 2017: The Next Era: Deep Learning for Biomedical Research

ICIC 2017:

ICIC 2017: Freeware and public databases: Towards a Wiki Drug Discovery?

ICIC 2017: New product presentations CAS

ICIC 2017: Dealing with Patent Families in FTO Searches, Portfolio Analysis a...

ICIC 2017: New Poduct presentations CFL Software

ICIC 2017: New Product Introduction info apps

ICIC 2017: New product presentation EXPERT SYSTEM

ICIC 2017: Looking at the gift horse: pros and cons of over 20 million patent...

ICIC 2017: New Poduct presentations BizInt

Similar a ICIC 2017: New product presentationsLighthouse IP

II-PIC 2017 in Bangalore

Dr. Haxel Consult

Are there any frontiers left in patent data? Richard Garner (LexisNexis, UK) As we have gradually tackled the major challenges in patent data gathering over the past years, the question is: what is the next frontier? Are there any important countries left to be integrated? After translating Chinese, Japanese and Korean patent data in Full text and continuously on the frontfiles, is Asian Patent data ‘unlocked’? And then after that? Where is the next frontier? In this presentation we will present our vision on what data will impact patent research in the future and which technological or data developments have the most impact on the possibilities we have in the near and distant future.

ICIC 2013 Conference Proceedings Richard Garner (LexisNexis)

Dr. Haxel Consult

Yole led phosphor_qd_ip_january_2016_sample

Clotilde Fabre

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 150 countries coverage for patents and trademarks. Lighthouse IP data is available via several partners. The company is headquartered in Amsterdam-Schiphol 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. Patent Global Bibliographic and Legal Data Collection (DIAMOND) Lighthouse IP currently directly sources the official gazette of over 150 different countries.Data is created manually from the gazettes as soon as they are published. This enables Lighthouse IP to provide a stable and reliable data feed for many additional national offices available from other sources. The collection includes inventions and utility models. There are two separate data products offered, one for the bibliographic data and one for the legal data. The data is delivered in XML format base on the WIPO standards ST.9 and ST.17 for bibliographic and legal event data published in the gazettes. English translations and original text data are provided along with normalized names of persons and companies. Patent Full Text Collection Lighthouse IP has specialized in creating the largest collection of full text searchable patents. Currently the coverage offers access to more than 70 authorities. All of these XML files include original versions of the patent document and machine translations into English. Updating for all authorities is regular and in line with the publication frequency of the national office. Trademark Collection The Lighthouse IP Trademark Collection contains the data of 150 authorities. For all authorities backfile and frontfile are created, and made available in data feeds based on XML structures. Including translated owner names, classes, lists of goods and services and all relevant meta data, this collection is unique for use in trademark research. PatentWarehouse.com ™ Image and XML archive Via the PatentWarehouse.com platform Lighthouse IP provides API access to the world’s largest repository of patent publications in PDF format. For all its full text holdings Lighthouse IP has added the original full records and machine translations in XML format.

AI-SDV 2021: Lighthouse IP

Dr. Haxel Consult

AI-SDV 2022: Lighthouse IP

Dr. Haxel Consult

Watch full webinar here: https://buff.ly/3Cgntpf Data that is increasingly distributed across on-premises and multiple cloud platforms offers both opportunities and challenges for insights-driven business decision making. This is true for any industry and any organization, small or large. While modern data architectures such as data fabric or data mesh offer innovative solutions to extract maximum value from organizational data, in many instances physical replication or consolidation of data makes those solutions ineffective. In this session Paul Moxon, SVP of Data Architecture and Chief Evangelist at Denodo will present a number of customer examples illustrating how organizations have successfully implemented a logical data architecture.

Transforming Data Management in the Cloud with the Denodo Platform

Denodo

So, China - Buyers Sellers Litigation

Erik Oliver

Zephyr M&A database

dumouche

Maximizing and protecting ip

eophiladelphia

Maximizing and protecting ip

Nerve2012

Information sources for Patent Searching

IP Models for Africa

GOV-Geocode Data

International ipr

International intellectual property rights

Vijay Vj

KEY FEATURES OF THE REPORT The report provides essential patent data for FD-SOI including: • Time evolution of patent publications and countries of patent filings. • Current legal status of patents. • Ranking of main patent applicants. • Joint developments and IP collaboration network of main patent applicants. • Segmentation by architecture (planar FD-SOI, SOI FinFET) and process level (transistor, device, circuit). • Key patents. • Granted patents near expiration. • Relative strength of main companies IP portfolio. • Matrix applicants / technology segments. • FD-SOI IP profiles of major companies with key patents, patented technologies, partnerships, and IP strength and strategy. The report also provides an extensive Excel database with all patents analyzed in the study. OBJECTIVE OF THE REPORT • Provide an overview of FD-SOI technology. • Review context for FD-SOI technology. • Understand the patent landscape for FD-SOI. • Identify key patents of FD-SOI technology. • Understand trends in FD-SOI IP. • Identify the major players in FD-SOI IP and the relative strength of their patent portfolio. • Identify new players in FD-SOI IP. • Identify IP collaboration networks between key players.

Sample FD SOI Patent Landscape

Knowmade

Ken Seddon, LOT Network: Protecting the Financial Services Industry from (Open Source) Patent Trolls. Companies spend over $29B each year on legal costs defending themselves against patent trolls. Over half of companies targeted by trolls make less than $10M in annual revenue — and companies engaging in software — like those involved in open source development — are the most likely to be sued. LOT Network CEO Ken Seddon will bring a panel of speakers from member companies such as SAP, Google, JP Morgan Chase and Dropbox to share strategies on how companies in the open source community can protect themselves from costly and frivolous litigation that drains funds away from innovation.

Protecting the Financial Services Industry from (Open Source) Patent Trolls

FINOS

界昇 20151007 ira_cognizer

景逸王

Querying Patent Data for Empirical Scholarship : Tools and Strategies

Professor Jon Cavicchi, UNH School of Law

WilliamCass_Inside3DPrintingSingapore

MecklerMedia

Similar a ICIC 2017: New product presentationsLighthouse IP (20)

II-PIC 2017 in Bangalore

ICIC 2013 Conference Proceedings Richard Garner (LexisNexis)

Yole led phosphor_qd_ip_january_2016_sample

AI-SDV 2021: Lighthouse IP

AI-SDV 2022: Lighthouse IP

Transforming Data Management in the Cloud with the Denodo Platform

So, China - Buyers Sellers Litigation

Zephyr M&A database

Maximizing and protecting ip

Information sources for Patent Searching

IP Models for Africa

GOV-Geocode Data

International ipr

International intellectual property rights

Sample FD SOI Patent Landscape

Protecting the Financial Services Industry from (Open Source) Patent Trolls

界昇 20151007 ira_cognizer

Querying Patent Data for Empirical Scholarship : Tools and Strategies

WilliamCass_Inside3DPrintingSingapore

Más 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.

Dr. Haxel Consult

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: New Product Introductions: CENTREDOC

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

Más de Dr. Haxel Consult (20)