AI-SDV 2021 Biomax
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Biomax Informatics provides services and software solutions for efficient decision making and knowledge management at the intersection of life sciences, healthcare and information technologies. Biomax facilitates digital transformation within biotech, pharma, agriculture, food and chemical industries as well as research institutes. Biomax offers a range of standard products, based on the core technology knowledge management technology BioXM™, which are synergistically interrelated. AILANI™, the Artificial Intelligence LANguage Interface, provides unique semantic search capabilities that catalyze digital change and accelerate the innovation cycle. NeuroXM™ is the one-stop-shop to decipher brain physiology. The Clinical Integration System ensures access to real world evidence data, which is critical to effectively and robustly train Artificial Intelligence to support clinical decision support at the point of care. With more than 20 years of experience and around 50 employees - including numerous life scientists, data scientists and software developers with a scientific background - Biomax is a competent partner. Founded in 1997, Biomax is ISO 9001 and ISO 27001 certified and is headquartered in Planegg near Munich, Germany. More info @ www.biomax.com
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This document introduces PatentStrategiesSM, a tool from LexisNexis that correlates over 90 million worldwide patents with various data sources to provide a comprehensive view of the intellectual property landscape. It analyzes patent and business data using over 50 visualizations to help with research and innovation, licensing, competitive analysis, litigation, acquisitions, risk management, and strategic planning. Key capabilities include examining patent strength, creating datasets based on semantics or other criteria, understanding patent expiration status, analyzing markets and technology areas through various maps and visualizations, and clustering related patents. The tool aims to provide insights that previously took days or weeks to uncover in just minutes.
AI-SDV 2020: AI-augmented Question Answering and Semantic Search for Life Sci...
We have created structure based chemical ontologies that are used to classify chemical compounds automatically. These classifications can be used with success in semantic search engines to find all representatives of a chemical class. In the present paper we would like to demonstrate use cases when utilizing these chemical classes as features in typical machine learning approaches.
Thus, we have used the co-occurrence of chemical compounds with biological and physico-chemical properties in scientific articles to train models that predict properties of novel compounds that did not occur in those training sets. One example is the prediction of hepatotoxicity as well as bioavailability. In principle, one can use any property that is found in the textual vicinity of compounds to build such predictive models. Criteria will be presented that allow to judge the quality and predictive power of such models.
II-SDV 2015, 20 - 21 April, in Nice
This document discusses exploring patent citations and their benefits and challenges. It begins by noting that while citations provide valuable information, they can be complex and underused. It then provides details on what a patent citation is, where citation data comes from, and why citations are useful for finding related patents, analyzing patent portfolios, competitor monitoring, and identifying licensing opportunities. Finally, it acknowledges some pitfalls like data quality and coverage issues but emphasizes that citations are a valuable resource when used properly.
II-SDV 2014 Automated Relevancy Check of Patents and Scientific Literature (K...
Dr. Philipp Daumke presents Averbis, a company that leverages structured and unstructured data through natural language processing and machine learning. Their tools can automatically categorize patents and research literature at scale to help with market analysis, competitor monitoring, and portfolio management. Their machine learning systems are trained on labeled data to imitate how experts classify information. Case studies demonstrate how their tools can save up to 80% of the time spent on tasks like patent landscaping compared to manual labeling, with similar levels of accuracy.
ICIC 2014 New Product Introduction LexisNexis
The document describes PatentAdvisor, a tool that provides data-driven insight into the US patent prosecution process. It allows law firms to understand how their patent applications are progressing compared to averages, providing detailed insight into the application to grant timeline. This includes metrics like office action numbers, allowance rates, time to issue, and budgets. PatentAdvisor helps firms create stronger applications, monitor their portfolio performance, manage prosecution strategy and budgets, and review law firm quality.
Biased Information Retrieval in Pharmaceutical Drug Development
Pharmaceutical companies are highly dependent on access to high quality information retrieval. Insufficient gathering and selection of scientific information could potentially impact corporate decision-making in a wrong direction.
To assess the value of external information retrieval services a number of third party information providers were contacted with two information research requests (within inflammatory diseases). The providers were asked to return with search results and search methodologies used. In the first search the interaction with the providers were kept at a minimal level, whereas in the second search the contact, direction, and interaction were increased.
It is concluded that information research results from different providers are variable. The expected increase in inter-homogeneity of results from the different providers could not be confirmed after the second search. The overall overlap of results was 38% for the first search and 33% for the second search, and surprisingly none of the references were found by all providers.
To fully cover the area of interest and to avoid bias it is recommended to perform exhaustive scientific literature searches. Researchers and decision-makers should accept large amounts of results from literature searches and promote initiatives to analyse these results in detail.
ICIC 2014 Tracking of the Mode of Action Landscape in Breast Cancer using Rep...
Assessment of the “Mode of Action Landscape” for particular disease areas is of high interest for pharmaceutical companies. To enable identification of upcoming, established and vanishing modes of action over time and clinical phases it is crucial to have tools for integration and comparison of drug pipeline data from various sources, including informative visualizations of changes in the landscape.
The BizInt Smart Charts product family including VantagePoint - Smart Charts Edition (VP-SCE) enables these analyses and was therefore selected for evaluation. Data was integrated from different key drug pipeline databases, and the newly developed VP-SCE provided opportunities to use in-house data for normalization of important field content such as the highly diverse lists of “Mode of Action” generated by the pipeline databases. Using an example of pipeline data in the field of breast cancer we will show how the data was curated and processed to reach the final landscape, and how the programs can be applied in the most effective way. Examples of visualizations for facilitated decision-making will also be shown. To this end, our presentation will provide insight on the value of integrating and visualizing both external and internal data from drug pipelines employing these tools.
II-SDV 2017: Gridlogics Technologies
Gridlogics is a leading provider of products and custom software solutions for patent research, management, data analysis and project management. Our products leverage the latest techniques in information retrieval, data mining and visualizations to help clients globally in deriving actionable intelligence from the masses of patent data.
IC-SDV 2018: Aleksandar Kapisoda (Boehringer) Using Machine Learning for Auto...
Focusing on the significance of targets is one of the key drivers for quality of web search.
Filtering targeted companies based on the significance of their business model for the expected search results was one of our “nice to haves” last year.
Evaluating a number of artificial intelligence approaches based on neural networks, classical machine learning and semantic technologies lead us to a working hybrid approach.
IC-SDV 2019: Minesoft
Minesoft, founded in 1996, develops patent information services and solutions, linking technical, legal, bibliographic and full text patent information for patent professionals and research specialists.
Minesoft's products and services are used by leading corporations, national Patent Offices, patent attorneys and law firms globally.
Minesoft develops fast, effective document delivery solutions, a range of competitive intelligence services including patent alerting and monitoring tools, a patent family & legal status portal delivering the latest data for over 40 countries, a searchable patent database of over 48 million records, patent archiving, advanced viewing tools and more.
In May 2003, Minesoft and RWS announced their agreement to develop PatBase, a new searchable patent database designed by experts in the complex art of search and retrieval of patent information. The first public demonstrations of PatBase in November 2003 received critical acclaim from expert patent searchers for the intuitive and feature-rich interface. PatBase is a comprehensive new search resource for patent and R&D specialists worldwide, covering 100 countries.
Organised into extended patent families, each invention is represented by one individual record, making it easy to see in which countries a filing for patent protection has been made. PatBase is an ideal resource for conducting daily patent & technology searches. Rapid delivery of competitive intelligence, integrated searchable full text, PDF delivery and legal status reports bring PatBase to the forefront of today's searchable patent information tools. PatBase is regularly updated with new data and new search features and is now established as a leading patent resource.
PatBase Express, developed in partnership with RWS and released March 2006, provides an easy-to-use end-user corporate-wide solution. PatBase Express allows the most up-to-date scientific research and competitor information contained in patent documents to be accessed throughout an organisation.
Minesoft products can be customised to individual corporate requirements.
Find more on www.minesoft.com
Monitoring and Analysis of Web Information for Various Business Contexts : Co...
A range of business use cases will be presented for illustrating the combined use of several technologies and tools including web content crawling and monitoring, advanced information search and retrieval, information analytics and information delivery developed by Qwam.
Use cases presented will cover :
Automated gathering and extraction of corporate web information for competitive intelligence, CRM systems, lead generation, etc.
Building knowledge base with selected web information for marketing intelligence needs
Information analytics of content and usage with knowledge portal applications
ICIC 2013 Conference Proceedings Tony Trippe Patinformatics
The document discusses how big data and data science techniques are bringing a "sea change" to patent analytics. These new techniques, like Hadoop and R, allow for analyzing the huge amounts of patent data in ways that were not possible before. Examples discussed include next-generation citation analysis using network diagrams, word trees to analyze patent claims, and tag clouds for discovering hedge words and synonyms. The advent of these big data analytics tools is creating new opportunities for growth in the patent analysis field.
IC-SDV 2018: Search Technology / VanatagePoint
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The Venue Hotel
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Search Technology VantagePoint
For over 30 years, Search Technology, Inc. has helped our customers turn information into knowledge. We provide software tools and services that extract more value from patent, scientific, technical and business databases. Our primary product, VantagePoint, helps you rapidly understand and navigate through search results, giving you a better perspective - a better vantage point - on your information. Discover why many of today’s Fortune 100 companies use VantagePoint to help them succeed. VantagePoint is Serious Software for Serious Professionals.
Commercializing Alternative Data
Overview of end-to-end lifecycle to productize and commercialize alternative datasets at S&P Global Market Intelligence
Benefits to discuss:
How S&P Market Intelligence develops new alternative datasets
How S&P Market Intelligence develops robust production processes for alternative data
S&P Global Market Intelligence GTM strategy and capabilities to sell alternative data
AI-SDV 2020: Can There Be Profitable Revenue from an AI Deployment? The Upsid...
In the last twelve months AI activity has continued to accelerate. While there have been major setbacks in AI over the decades its recent up surge seems to be holding. Many positives stories are hitting the news, but is anyone actually making any money on AI deployments besides the big AI vendors? Have there been significant, meaningful cost reductions from AI deployments? Yes! Brief case studies will be presented from primary and secondary sources illustrating impacts on real world cost savings and revenue enhancements. As is always the case with real world projects there are lessons learned!
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ICIC 2017: Technology Scouting: Decision Support in Strategic Analyses for Te...
ICIC 2017: Technology Scouting: Decision Support in Strategic Analyses for Te...
AI-SDV 2020: Delivering AIM™ Patent Landscapes for Competitive Intelligence –...
AI-SDV 2020: Delivering AIM™ Patent Landscapes for Competitive Intelligence –...
AI-SDV 2020: AI-augmented Question Answering and Semantic Search for Life Sci...
AI-SDV 2020: AI-augmented Question Answering and Semantic Search for Life Sci...
II-SDV 2014 Automated Relevancy Check of Patents and Scientific Literature (K...
II-SDV 2014 Automated Relevancy Check of Patents and Scientific Literature (K...
Biased Information Retrieval in Pharmaceutical Drug Development
Biased Information Retrieval in Pharmaceutical Drug Development
ICIC 2014 Tracking of the Mode of Action Landscape in Breast Cancer using Rep...
ICIC 2014 Tracking of the Mode of Action Landscape in Breast Cancer using Rep...
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IC-SDV 2018: Aleksandar Kapisoda (Boehringer) Using Machine Learning for Auto...
Monitoring and Analysis of Web Information for Various Business Contexts : Co...
Monitoring and Analysis of Web Information for Various Business Contexts : Co...
ICIC 2013 Conference Proceedings Tony Trippe Patinformatics
ICIC 2013 Conference Proceedings Tony Trippe Patinformatics
AI-SDV 2020: Can There Be Profitable Revenue from an AI Deployment? The Upsid...
AI-SDV 2020: Can There Be Profitable Revenue from an AI Deployment? The Upsid...
Similar to AI-SDV 2021 Biomax
PatSeer Overview
This document provides an overview of the PatSeer patent research and analysis platform. Some key points:
- PatSeer has over 89 million full text patent records covering 65 countries and 127 million bibliographic records covering over 100 countries.
- It features a hybrid search engine allowing publication, family, and application based searches. Tools include an AI-powered NLP search engine, assignee/inventor search aids, and litigation data integration.
- Users can analyze results, set up alerts, and collaborate on projects with customizable fields, ratings, and interactive dashboards for sharing insights across teams.
How to Jump Start Taxonomy Content Creation webinar slides 9 24 15
This document discusses how to create taxonomy content and metadata. It defines taxonomy and tagging, outlines common challenges around content findability, and the value of metadata. It provides guidance on getting started with taxonomy development including understanding user needs, business involvement, and governance. The presentation then demonstrates WAND and Expert System's combined software solution for importing taxonomies, visualizing content to inform taxonomy structure, automatically generating rules for categorization, and deploying taxonomies for enterprise search and knowledge management applications.
Rethink Analytics with an Enterprise Data Hub
Have you run into one or more of the following barriers or limitations with your existing data warehousing architecture:
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> Lack of analytics agility?
Using the power of OpenAI with your own data: what's possible and how to start?
This document provides an overview of a talk by Maxim Salnikov and Jon Jahren at Oslo Spektrum from November 7-9. It discusses using OpenAI with your own data and how to get started. Examples of enterprise use cases for generative AI are presented, such as chatbots, document indexing, and financial analysis. Tools for prompt engineering like LangChain and Semantic Kernel are introduced. Best practices for fine-tuning models on proprietary data are covered, including data formatting, training data size, and an iterative tuning process. Responsible AI techniques like grounding responses and maintaining a positive tone are also discussed.
Business searching for engineering 185 fri am power point april 17 2015
Basic business information research, with a particular emphasis on finding information about consumer markets.
Lean Security
We have a lot to do on the cybersecurity side, and we are almost always lacking people, or budget, or both. Can we take lessons and approaches from entrepreneurship to apply to our cybersecurity programs? Can we do more with what we have, or for each addition can we make sure it has a large impact?
We’ll explore some entrepreneurship principles and then dive into some ways to improve security without large increases in headcount or budget.
Welcome to a new state of find
Like most modern organizations, your teams are likely using upwards of 10 cloud-based applications on a daily basis, but spending far too many hours a day searching for the information they need across all of them. With the out-of-the-box capabilities of Elastic Workplace Search, see how easy it is to put relevant content right at your teams’ fingertips with unified search across all the apps they rely on to get work done.
OK So Enterprise Search is "Janky" - Now What?
Search for the enterprise seems to have hit a wall. Bad search is the top complaint of users interacting with their internal data. Meanwhile, there is a seemingly never-ending flood of products, SaaS offerings and new solutions in the market all claiming and attempting to solve the problem.
In this roundtable, we will define what expectations organizations should really have about their search platforms and discuss what benefits to expect from using techniques like boosting, auto-classification, natural language processing, query expansion, entity extraction and ontologies. We will also explore what will supersede search in the enterprise.
Oltre l’intelligenza Artificiale: agire alla velocità del pensiero
In questo Webinar racconteremo come l’intelligenza cognitiva di IBM Watson si affianca alle Università e ai Centri di Ricerca per potenziare gli skill e le capacità di analisi e di comprensione dei dati e delle informazioni.
Dare risposte concrete a problemi che incidono sulla nostra vita e il nostro lavoro, accedere ad un livello di conoscenza superiore grazie a nuove capacità cognitive anche questo è il nuovo modo di IBM per aiutare le Università e la Ricerca.
Realize Greater "Return on Information" with Google Enterprise Search
Google and Perficient together present this webinar about the benefits of deploying enterprise search; How search architecture solutions such as Google's Enterprise Search products aid in quicker retrieval of enterprise data and information.
Business searching for engineering 185 fri am power point october 16 2015
The document discusses strategies for locating business information, including developing an efficient research strategy and finding various types of information. It outlines how to find industry and company information using databases like IBISWorld and MarketLine that provide reports on industries and companies. It also discusses how to find information about markets and consumers using databases like Business Source Complete, Factiva, and MarketResearch.com, as well as tools like SimplyMap for demographic data. Finally, it outlines resources for finding government information about regulations, consumers, and product safety from sources like the U.S. Census, Electronic Code of Federal Regulations, and U.S. Consumer Product Safety Commission.
Optus improves customer experience
Optus, an Australian telecommunications company, implemented HP IDOL to consolidate its disparate search systems and improve customer experience. HP IDOL provided a single search platform that could search across Optus' enterprise systems and websites. This resulted in more relevant search results, a tenfold increase in search usage, and lower costs compared to maintaining multiple search systems. The implementation was a success, improving the customer experience through faster, more unified search capabilities.
FutureLinks - AI-powered Digital Research Assistant
utureLinks is a multi-disciplinary, AI and Machine Learning-powered aggregator for academic papers, and journals. It will provide a personalized and customized experience to researchers, students and scholars giving them access to millions of journals from disciplines of their choosing. Future Links will not just be the one-stop-platform for researchers, but it will also spur readership and exposure of journals.
Business searching for engineering 185 fri am power point january 23 2015
This document provides an overview of strategies and sources for conducting business research. It discusses developing an efficient research strategy, finding industry and company information, market and consumer information, and government regulations. Specific databases and resources are demonstrated for locating industry reports, company profiles, market research, demographic data, and information on product regulations. Attendees are encouraged to follow up with the librarian if they have any other questions.
London Online 2008
The document discusses challenges in innovation and information retrieval. It introduces illumin8, a natural language processing tool that can search billions of web pages, articles, and patents. Unlike keyword searches, illumin8 understands meaning and can extract problems, solutions, and benefits. It has helped R&D professionals at major companies efficiently find relevant information across large amounts of technical data.
Ria Sankar - How to Build Winning Products - Product School Bellevue - 83018
ProductSchool offers part-time courses in product management, coding, data, digital marketing, and blockchain in 14 campuses across cities in the US, Canada, and the UK, as well as online. It has graduated over 5,000 alumni. The speaker discusses various product management frameworks like Jobs Theory, Blue Ocean Strategy, Porter's Five Forces, BCG Matrix, and Kano Model. She also covers different user research methods like focus groups, surveys, remote studies, message testing, and cohort analysis. The presentation concludes with discussing Lean UX and AARRR metrics.
Class, The COSO framework of internal controls is practiced .docx
Class,
The COSO framework of internal controls is practiced within companies around the world. The objectives of the COSO framework are closely related to its five components. For this week’s activity, please discuss these five components of the COSO framework. Be sure to include each components’ impact on each of the COSO framework objectives. What do you feel an auditor would most be concerned with during an IT audit? Lastly, discuss suggestions for integrating COSO framework compliance into a company in which you are familiar.
Your paper should meet the following requirements:
• Be approximately 2-4 pages in length, not including the required cover page and reference page.
• Follow APA6 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.
• Support your answers with the readings from the course and at least two scholarly journal articles to support your positions, claims, and observations, in addition to your textbook. The UC Library is a great place to find resources.
• Be clearly and well-written, concise, and logical, using excellent grammar and style techniques. You are being graded in part on the quality of your writing.
Managing and Using Information Systems:
A Strategic Approach – Sixth Edition
Keri Pearlson, Carol Saunders,
and Dennis Galletta
© Copyright 2016
John Wiley & Sons, Inc.
Chapter 12
Knowledge Management, Business Intelligence, and Analytics
2
Opening Case: Netflix
What gave Netflix assurance that House of Cards would be a success?
What gives Netflix a competitive advantage?
© 2016 John Wiley & Sons, Inc.
3
Data from 33 million people provided strong evidence that the British version was very popular and Kevin Spacey was also a popular actor
Again, data from millions of users, showing what they watch, when they pause, when they rewind, etc. Patterns emerge that speak volumes about preferences. Their analytics algorithms provide better data than focus groups (and in real time).
3
More Real World Examples
Caesar’s and Capital One both collect and analyze customer data.
Result: They can determine who are the most profitable customers and then follow up with them.
Caesar’s: frequent gamblers
Capital One: charge a lot and pay off slowly
They provide products that would appeal to the profitable customers.
© 2016 John Wiley & Sons, Inc.
4
4
A Real World Example from Sports
Oakland As and Boston Red Sox baseball teams
Crunched the numbers on the potential players, such as on-base percentage
Others who did not do the analysis failed to recognize the talent
© 2016 John Wiley & Sons, Inc.
5
5
Five Ways Data Analytics can Help an Organization (McKinsey and Co.)
Making data more transparent and usable more quickly
Exposing variability and boosting performance
Tailoring products and services
Improving decision-making
Improving products
© 2016 John Wiley & Sons, Inc.
6
Terminology
Knowledge management: The processes needed ...
Class, The COSO framework of internal controls is practiced .docx
Class,
The COSO framework of internal controls is practiced within companies around the world. The objectives of the COSO framework are closely related to its five components. For this week’s activity, please discuss these five components of the COSO framework. Be sure to include each components’ impact on each of the COSO framework objectives. What do you feel an auditor would most be concerned with during an IT audit? Lastly, discuss suggestions for integrating COSO framework compliance into a company in which you are familiar.
Your paper should meet the following requirements:
• Be approximately 2-4 pages in length, not including the required cover page and reference page.
• Follow APA6 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.
• Support your answers with the readings from the course and at least two scholarly journal articles to support your positions, claims, and observations, in addition to your textbook. The UC Library is a great place to find resources.
• Be clearly and well-written, concise, and logical, using excellent grammar and style techniques. You are being graded in part on the quality of your writing.
Managing and Using Information Systems:
A Strategic Approach – Sixth Edition
Keri Pearlson, Carol Saunders,
and Dennis Galletta
© Copyright 2016
John Wiley & Sons, Inc.
Chapter 12
Knowledge Management, Business Intelligence, and Analytics
2
Opening Case: Netflix
What gave Netflix assurance that House of Cards would be a success?
What gives Netflix a competitive advantage?
© 2016 John Wiley & Sons, Inc.
3
Data from 33 million people provided strong evidence that the British version was very popular and Kevin Spacey was also a popular actor
Again, data from millions of users, showing what they watch, when they pause, when they rewind, etc. Patterns emerge that speak volumes about preferences. Their analytics algorithms provide better data than focus groups (and in real time).
3
More Real World Examples
Caesar’s and Capital One both collect and analyze customer data.
Result: They can determine who are the most profitable customers and then follow up with them.
Caesar’s: frequent gamblers
Capital One: charge a lot and pay off slowly
They provide products that would appeal to the profitable customers.
© 2016 John Wiley & Sons, Inc.
4
4
A Real World Example from Sports
Oakland As and Boston Red Sox baseball teams
Crunched the numbers on the potential players, such as on-base percentage
Others who did not do the analysis failed to recognize the talent
© 2016 John Wiley & Sons, Inc.
5
5
Five Ways Data Analytics can Help an Organization (McKinsey and Co.)
Making data more transparent and usable more quickly
Exposing variability and boosting performance
Tailoring products and services
Improving decision-making
Improving products
© 2016 John Wiley & Sons, Inc.
6
Terminology
Knowledge management: The processes needed.
How Machine Learning Will Transform Finance
In this presentation you will learn about emerging technology and how it can be applied to finance function and how to start your journey of becoming an Adaptive Enterprise.
Microsoft and Enterprise Search
Sean Coleman discussed the three major enterprise search options available from Microsoft: Office 365/SharePoint, Bing for Business, and Azure Search. Each option has strengths and weaknesses. Office 365/SharePoint offers classic and modern search within SharePoint but has limitations. Bing for Business provides a personalized search experience starting with Bing. Azure Search is a search-as-a-service cloud solution that offers flexibility but has fewer out-of-the-box features. Future developments may blend the capabilities of these options.
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How to Jump Start Taxonomy Content Creation webinar slides 9 24 15
How to Jump Start Taxonomy Content Creation webinar slides 9 24 15
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Business searching for engineering 185 fri am power point april 17 2015
Oltre l’intelligenza Artificiale: agire alla velocità del pensiero
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Business searching for engineering 185 fri am power point october 16 2015
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Business searching for engineering 185 fri am power point january 23 2015
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Ria Sankar - How to Build Winning Products - Product School Bellevue - 83018
Ria Sankar - How to Build Winning Products - Product School Bellevue - 83018
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Class, The COSO framework of internal controls is practiced .docx
Class, The COSO framework of internal controls is practiced .docx
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This document describes a metadata list of patent holders in various countries and regions compiled by Muchiu (Henry) Chang. The list is sorted geographically and includes patent holder names from Canada, China, Hong Kong, Macao, Taiwan, the Middle East, and Europe between 2009-2022. Key features include Chinese-English compatibility and use of open source intelligence. The list has previously been utilized by the Region of Peel in Ontario, Canada.
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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.
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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.
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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.
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AI-SDV 2022: Embedding-based Search Vs. Relevancy Search: comparing the new w...
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Kornel Marko (Averbis, Germany)
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
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: New Insights from Trademarks with Natural Language Processing Al...
This document discusses using natural language processing on trademark text data to gain insights. It presents research on how trademark activity changed during COVID-19, detecting emerging trends in trademarks over time, and classifying trademarks by industry. The research uses techniques like topic modeling and deep learning classifiers to analyze trademarks and identify patterns. The analysis of trademarks can provide economic indicators and reveal where businesses are focusing their innovation and market presence.
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
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: Scientific publishing in the age of data mining and artificial i...
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: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
This document discusses using AI tools to improve patent search and analysis. It provides metrics on how well an AI system called IPscreener can retrieve patent citations compared to examiners. The metrics show recall rates increase with longer input text and when users provide additional context. Machine translation negatively impacts performance, but the AI can help users navigate patents by selecting relevant text segments. The goal is for AI to boost innovation by improving how users search for and understand prior art.
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
How do you find video when you only have sparse data? While you can wander the stacks (if you can still find open stacks) for inspiration, video either physical or digital, is difficult to discover. Wandering the virtual stacks is, well, virtually impossible. Discovery platforms on the whole have not replicated the inspirational experience of wandering the stacks.
More companies are using archivable video for internal communication of the various research projects, product developments, test results, and more that are being considered, in progress, or completed. Showing how an experiment was conducted can convey considerably more information that is very difficult to communicate via text. How do you find a company video that might be helpful for your project?
A case study is presented of the problems and the solutions that were implemented by a large, multinational chemical company. A suite of content discovery technologies was used including a video to text to tagging system connected to their documents database and automatically indexed using several chemical as well as conceptual systems (rule-based, NLP, inference engine). To build the system and support the manuscript and video submission there is a metadata extraction program which pulls and inserts the metadata into the submission forms so the author can move quickly through that process.
AI-SDV 2022: Copyright Clearance Center
Copyright Clearance Center
A pioneer in voluntary collective licensing, CCC (Copyright Clearance Center) helps organizations integrate, access, and share information through licensing, content, software, and professional services. With expertise in copyright and information management, CCC and its subsidiary RightsDirect collaborate with stakeholders to design and deliver innovative information solutions that power decision-making by helping people integrate and navigate data sources and content assets. CCC recently acquired the assets and technology of Deep SEARCH 9 (DS9), a knowledge management platform that leverages machine learning to help customers perform semantic search, tag content, and discover new insights.
AI-SDV 2022: Lighthouse IP
Lighthouse IP is the world’s leading provider of intellectual property content. The core business of Lighthouse IP is sourcing and creating content from the world’s most challenging authorities. Specialized in IP data, Lighthouse IP provides over 160 countries coverage for patents, over 200 authorities for trademarks and over 90 authorities for designs. Lighthouse IP data is available via several partners. The company is headquartered in Schiphol-Rijk in the Netherlands and has offices in the United States, China, Thailand, Vietnam, Egypt, Indonesia and Belarus. Globally a team of 150 experts works on the creation of this unique data collection.
AI-SDV 2022: New Product Introductions: CENTREDOC
CENTREDOC was created in 1964 as the technical information center of the swiss watchmaking industry. Building on a strong team of engineers, CENTREDOC now offers a complete range of services and solutions for the monitoring of strategic, technological and competitive information. CENTREDOC is also a leader in the research of patent, technical and business intelligence, and offers consulting expertise in the implementation of monitoring solutions.
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
The everyday use of AI-driven algorithms for data search, analysis and synthesis comes with important time savings, but also reveals the need to understand and accept the limitations of the technology. Practical deployments on concrete topics are inevitable to assess and manage the challenges of neuronal network based AI. A workshop report.
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
What if there was a platform where literature, conference abstracts, patents, clinical trials, news, grants and other sources were fully integrated? What if the data would be harmonized, enriched with standardized concepts and ready for analysis? After building our patent analytics platform we didn’t stop dreaming and built our big data analytics platform by semantically integrating text-rich, scientific sources. In my presentation I will talk about what we built and why we built it. And, of course, I will also address the challenges and hurdles along the way. Was it worth it and what comes next? Let’s talk about it!
More from Dr. Haxel Consult (20)
AI-SDV 2022: Henry Chang Patent Intelligence and Engineering Management
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AI-SDV 2022: Creation and updating of large Knowledge Graphs through NLP Anal...
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AI-SDV 2022: The race to net zero: Tracking the green industrial revolution t...
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AI-SDV 2022: Rolling out web crawling at Boehringer Ingelheim - 10 years of e...
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AI-SDV 2022: Machine learning based patent categorization: A success story in...
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AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: Finding the WHAT – Will AI help? Nils Newman (Search Technology,...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: New Insights from Trademarks with Natural Language Processing Al...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Extracting information from tables in documents Holger Keibel (K...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: Scientific publishing in the age of data mining and artificial i...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: AI developments and usability Linus Wretblad (IPscreener / Uppdr...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Where’s the one about…? Looney Tunes® Revisited Jay Ven Eman (CE...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Possibilities and limitations of AI-boosted multi-categorization...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
AI-SDV 2022: Big data analytics platform at Bayer – Turning bits into insight...
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SLU毕业证原版定制【微信：176555708】【圣路易斯大学毕业证成绩单-学位证】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
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一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
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◇申请留学生创业基金
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1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
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7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
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CSU毕业证原版定制【微信：176555708】【加利福尼亚州立大学毕业证成绩单-学位证】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
◆◆◆◆◆ — — — — — — — — 【留学教育】留学归国服务中心 — — — — — -◆◆◆◆◆
【主营项目】
一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
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可查真实(Monash毕业证)西澳大学毕业证成绩单退学买
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二：真实使馆认证（留学人员回国证明）使馆存档
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2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
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6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
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如果您计划在国内发展那么办理国内教育部认证是必不可少的。事业性用人单位如银行国企公务员在您应聘时都会需要您提供这个认证。其他私营 #外企企业无需提供！办理教育部认证所需资料众多且烦琐所有材料您都必须提供原件我们凭借丰富的经验帮您快速整合材料让您少走弯路。
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假文凭国外(Adelaide毕业证)澳大利亚国立大学毕业证成绩单办理
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2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）
-办理真实使馆公证（即留学回国人员证明）
-办理各国各大学文凭（世界名校一对一专业服务,可全程监控跟踪进度）
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（详情请加一下 文凭顾问+微信:176555708）欢迎咨询！
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办理毕业证(UPenn毕业证)宾夕法尼亚大学毕业证成绩单快速办理
官方原版办理宾夕法尼亚大学毕业证【微信176555708】学历认证怎么做：原版仿制宾夕法尼亚大学电子版成绩单毕业证认证【宾夕法尼亚大学毕业证成绩单】、宾夕法尼亚大学文凭证书成绩单复刻offer录取通知书、购买UPenn圣力嘉学院本科毕业证、【宾夕法尼亚大学毕业证办理UPenn毕业证书哪里买】、宾夕法尼亚大学 Offer在线办理UPenn Offer宾夕法尼亚大学Bachloer Degree。（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
◆◆◆◆◆ — — — — — — — — 【留学教育】留学归国服务中心 — — — — — -◆◆◆◆◆
【主营项目】
一.毕业证【微信：176555708】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微信：176555708】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分→ 【关于价格问题（保证一手价格）
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
学历顾问：微信：176555708
Understanding User Behavior with Google Analytics.pdf
Unlocking the full potential of Google Analytics is crucial for understanding and optimizing your website’s performance. This guide dives deep into the essential aspects of Google Analytics, from analyzing traffic sources to understanding user demographics and tracking user engagement.
Traffic Sources Analysis:
Discover where your website traffic originates. By examining the Acquisition section, you can identify whether visitors come from organic search, paid campaigns, direct visits, social media, or referral links. This knowledge helps in refining marketing strategies and optimizing resource allocation.
User Demographics Insights:
Gain a comprehensive view of your audience by exploring demographic data in the Audience section. Understand age, gender, and interests to tailor your marketing strategies effectively. Leverage this information to create personalized content and improve user engagement and conversion rates.
Tracking User Engagement:
Learn how to measure user interaction with your site through key metrics like bounce rate, average session duration, and pages per session. Enhance user experience by analyzing engagement metrics and implementing strategies to keep visitors engaged.
Conversion Rate Optimization:
Understand the importance of conversion rates and how to track them using Google Analytics. Set up Goals, analyze conversion funnels, segment your audience, and employ A/B testing to optimize your website for higher conversions. Utilize ecommerce tracking and multi-channel funnels for a detailed view of your sales performance and marketing channel contributions.
Custom Reports and Dashboards:
Create custom reports and dashboards to visualize and interpret data relevant to your business goals. Use advanced filters, segments, and visualization options to gain deeper insights. Incorporate custom dimensions and metrics for tailored data analysis. Integrate external data sources to enrich your analytics and make well-informed decisions.
This guide is designed to help you harness the power of Google Analytics for making data-driven decisions that enhance website performance and achieve your digital marketing objectives. Whether you are looking to improve SEO, refine your social media strategy, or boost conversion rates, understanding and utilizing Google Analytics is essential for your success.
国外证书(Lincoln毕业证)新西兰林肯大学毕业证成绩单不能毕业办理
退学办理新西兰林肯大学毕业证【微信176555708】学历认证怎么做：原版仿制新西兰林肯大学电子版成绩单毕业证认证【新西兰林肯大学毕业证成绩单】、新西兰林肯大学文凭证书成绩单复刻offer录取通知书、购买Lincoln圣力嘉学院本科毕业证、【新西兰林肯大学毕业证办理Lincoln毕业证书哪里买】、新西兰林肯大学 Offer在线办理Lincoln Offer新西兰林肯大学Bachloer Degree。1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：微信176555708我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
7完成交易删除客户资料
高精端提供以下服务：
一：新西兰林肯大学新西兰林肯大学毕业证文凭证书全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站可查
四：留信认证留学生信息网站可查
五：与学校颁发的相关证件1:1纸质尺寸制定（定期向各大院校毕业生购买最新版本毕,业证成绩单保证您拿到的是鲁昂大学内部最新版本毕业证成绩单微信176555708）
A.为什么留学生需要操作留信认证?
留信认证全称全国留学生信息服务网认证,隶属于北京中科院。①留信认证门槛条件更低,费用更美丽,并且包过,完单周期短,效率高②留信认证虽然不能去国企,但是一般的公司都没有问题,因为国内很多公司连基本的留学生学历认证都不了解。这对于留学生来说,这就比自己光拿一个证书更有说服力,因为留学学历可以在留信网站上进行查询!
B.为什么我们提供的毕业证成绩单具有使用价值？
查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。
不能毕业如何获得(USYD毕业证)悉尼大学毕业证成绩单一比一原版制作
挂科购买☀【悉尼大学毕业证购买】【微信176555708】【USYD毕业证模板办理】加拿大文凭、本科、硕士、研究生学历都可以做,二、业务范围：
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二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
国外毕业证、学位证、成绩单办理流程：
1、客户提供办理信息：姓名、生日、专业、学位、毕业时间等（如信息不确定可以咨询顾问：【微信176555708】我们有专业老师帮你查询）；
2、开始安排制作毕业证、成绩单电子图；
3、毕业证、成绩单电子版做好以后发送给您确认；
4、毕业证、成绩单电子版您确认信息无误之后安排制作成品；
5、成品做好拍照或者视频给您确认；
6、快递给客户（国内顺丰，国外DHL、UPS等快读邮寄）。
专业服务，请勿犹豫联系我！本公司是留学创业和海归创业者们的桥梁。一次办理，终生受用，一步到位，高效服务。详情请在线咨询办理,欢迎有诚意办理的客户咨询!洽谈。
◆招聘代理：本公司诚聘英国、加拿大、澳洲、新西兰、加拿大、法国、德国、新加坡各地代理人员，如果你有业余时间，有兴趣就请联系我们咨询【微信176555708】
没文凭怎么找工作。让您回国发展信心十足！
★、真实教育部学历学位认证；（一对一专业服务，可全程监控跟踪进度）
★、真实使馆认证，可以通过大使馆查询确认；（即教育部留服认证，不成功不收费）
★、毕业证、成绩单等材料，从防伪到印刷、水印到钢印烫金，高精仿度都是跟学校原版100%相同的；（敬请放心使用）
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Discover the benefits of outsourcing SEO to India
"Discover the benefits of outsourcing SEO to India! From cost-effective services and expert professionals to round-the-clock work advantages, learn how your business can achieve digital success with Indian SEO solutions.
Explore-Insanony: Watch Instagram Stories Secretly
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AI-SDV 2021 Biomax
- 1. www.biomax.com AILANI – the new semantic search machine a customer journey with AILANI
- 2. Challenges faced by Researchers and R&D Leaders Innovative and efficient research in the context of existing knowledge Get information for better strategic decisions in complex environment New targets and products, Shorter time to market Support for merger and acquisitions
- 3. Hurdles that need to be overcome >Huge amounts of in-house and public data >Exploding literature volume >Hundreds of databases and platforms >Data loss, when knowledge owner leaves the company
- 4. Our Solution: AILANI™ for semantic integration and search
- 5. Customer Journey of a global life science company with AILANI™
- 6. Some years ago… Huge amounts of data Limited search capabilities No guarantee for accessing the full – relevant content More than 20.000 employees world-wide Different levels of interest and access rights (Researcher, R&D Leaders) Content silos including structured and unstructured data
- 7. Our customer’s goal “Accelerate innovation through fast and comprehensive knowledge discovery” > Method: AI-powered semantic search engine, providing fast, easy and comprehensive knowledge discovery to researchers > Extract highly relevant inferred or hidden knowledge
- 8. Why did customer select Biomax? Life Science Expertise for high quality results Robust semantic search technology built on many years experience with knowledge management platforms Search incl. AI-based Question/Answering Extraction and searching of chemical information by OSR and OCR
- 9. The customer’s journey 01 02 03 04 Business Requirements Enabling all employees to always find the most relevant information by question, keyword or structure. Technical Requirements Make 600k internal documents easily accessible across the organization, plus several million external documents, plus daily update Project Tasks - Harmonize public ontologies and build custom ontologies - Build custom AI - for question answering - for concept matching - to identify chemical structures from images Positive Outcome - Corporate AI-based semantic search platform for public and internal data - A zero footprint solution for a safe and efficient data search - Insights to innovation and better strategic decisions
- 10. Today… > AILANI has been in productive use now for almost 3 years > It is a central tool for all research and product development activities > Currently more than 1.300 researcher use AILANI throughout their daily business, making around 600 searches a week > Better results than ever before, answering complex questions like: > What is the current knowledge on my new project? > Which experiments were done last year with compound X? > Were there quality any issues reported by production? > Find internal and external experts on my research challenge
- 12. AILANI for everybody Options include: • Free test accounte • Licensing • POC • Customized Solution AILANI Artificial Intelligence LANguage Interface Transform scattered information points into actionable knowledge: An intuitive one-stop-shop for accessing internal and public data from anywhere in a completely secure environment.
- 13. AILANI Cloud Features FREE PERSONAL PROFESSIONAL PRO TEAMS Phrase/ Concept/ AI search ✔ ✔ ✔ ✔ Chemical Search ✔ ✔ ✔ ✔ Search History ✔ ✔ ✔ Bookmarked Searches ✔ ✔ ✔ Scheduled Alerting ✔ ✔ ✔ Bookmarked Documents, Compounds, Genes, etc. ✔ ✔ ✔ Document, Compound, Gene, Answer Tagging & Notes ✔ ✔ ✔ Export of results as table ✔ ✔ ✔ Export into RIS file for reference management tools ✔ ✔ ✔ Subscribe to Newsfeeds ✔ ✔ ✔ Collaboration via shared Document Tagging and Notes ✔ Personalization pre-configured “persona” personalized “persona” personalized “persona”
- 14. AILANI Enterprise AILANI Enterprise Features SMALL MEDIUM LARGE Functionality of AILANI Cloud ✔ ✔ ✔ Public content ✔ ✔ ✔ Additional content optimized for pre- configured domains ✔ ✔ ✔ Proprietary content with batch upload of text-based documents on demand ✔ ✔ ✔ Integration of structured data resources on demand ✔ ✔ Proprietary content with direct „live“ integration of internal infrastructure (Document management systems, ELN, other structured DBs, etc.) ✔ Optical Structure Recognition on proprietary documents ✔ ✔ ✔ Custom AI Models ✔ Personalization personalized “persona” up to 3 personalized “persona” custom ontologies for domain specific “persona”
- 15. www.biomax.com Thank you! Contact Dr. Philipp Krubasik Philipp.Krubasik@biomax.com Tel: +49 89 895 574-842