MACHINE LEARNING PATENT LANDSCAPE with special focus on Medical Analytics
|
|
- Giles Mathews
- 7 years ago
- Views:
Transcription
1 MACHINE LEARNING PATENT LANDSCAPE with special focus on Medical Analytics Teqmine Demo Landscape INTRODUCING BIG DATA IPR INTELLIGENCE Demo
2 What you will discover in full Teqmine Technology Map Independent expert evaluation of your risk and strategic environment to support business development Comprehensive map and details on Emerging Trends, Business Dynamics Decision Support Data, including Freedom To Operate, Competition, Expected Rate of Patenting, and other critical business intelligence. Convince investors, your management or yourself with accurate and precise analytics Data and Evidence: Technology Trends. How big key technology areas are and what is expected rate of patenting. Key patents. List of patents that matter especially much to your technology and business. Key competitors. Translation, input suggestions, see also previous Data and Statistics. Consolidated evidence on sources of new technology by country, city, leading inventors, etc. Tools. Access and work with your map on line Visualization. Show where your patents are located and see where the competition is.
3 Machine Learning Patent Map Topic 7 Teqmine tools allow you to discover and document key patenting areas and technology trends clearly
4 TEQMINE APPROACH STAGE 1 7 million USPTO patents text mined for 'machine learning' in patent full text. Data Records: 23,947 STAGE 2 Verification of map focus Recordsfrom Stage 1 clustered into 15 Topics using Artificial Intelligence. Non relevant recoreds removed Final set: records. STAGE 3 Records 12,185 clustered into 10 areas STAGE 4 High accuracy identification of Client interest areas. Network visualization of patent landscape and final analysis. Online Results and Tools All Rights Reserved 2015
5 Machine Learning Technology Trend Machine Learning is rapidly expanding technology and growth is likely to increase *Teqmine Estimate based on current expected patenting rate Note: Data includes Grants , Applications
6 Machine Learning Patent Race Among Tech Giants, Patent Race is materializing among Tech Giants Machine Learning. Incumbents and newcomers are solidifying their patent positions *Teqmine Estimate based on current expected patenting rate Note: Data includes Grants , Applications
7 Machine Learning Main Technology Areas Teqmine uses AI to divide fulltext patents into easily recognized technology areas (topics) Machine Learning data is broken into 10 Topic Areas Unsupervised discovery can be enhanced with trained classification, e.g. IPC classes or expert evaluation Innovation frontier is migrating from data science to business and application areas Key Technology Areas for ML are: Query technology. Databases, cognitivie data, information retrieval, learning Classification. Meta data generation, training. See also previous Text processing. Translation, input suggestions, see also previous Sensors. In /output, data processing, smart systems, traffic, IoT. Image/s. Detection, recognition classification, meta data Location based services. Navigation, Mapping, geo tagging, etc. Medical analytics. Patient treatment, public health models, analytic processes, predictive diagnostics Emerging areas: Fintech, Vehicles
8 Machine Learning Technology Trends by Topic Topic 1 Sensors, IoT Topic 2 Classification Topic 7 Medical analysis Topic 8 Query & Search *three months of data
9 Machine Learning Patent Map Position Medical Machine Learning Patents Machine Learning for C Hepatitis, 2016 Physiological Monitoring Devices and Methods Using Optical Sensors, 2016 System and Method For Identity Confirmation Using Physiologic Biometrics to Determine A Physiologic Fingerprint, 2016 Teqmine tools allow you to illustrate the position of your undisclosed inventions and patents, and compare to competitors
10 Key Assignees Topic 7 Machine Learning in Medical Analytics Business / Product driven patenting to increase quickly Key players look to solidify patent positions and accelerate innovation Patent risks to increase in the near future
11 Inventor Countries Topic 7 Machine Learning in Medical Analytics The US is innovation leader Innovation in Medical Machine Learning will be a global phenomenon in the near future. Ireland, Canada, Germany, and the Netherlands are especially important sources of new inventions in the next few years
12 Contact and more info Hannes Toivanen Tel Teqmine Analytics Pasilanraitio Helsinki Finland
Delivering Smart Answers!
Companion for SharePoint Topic Analyst Companion for SharePoint All Your Information Enterprise-ready Enrich SharePoint, your central place for document and workflow management, not only with an improved
More informationIntroduction to PatBase
Introduction to PatBase Overview A single, global patent family database Launched in October 2003 by Minesoft and RWS Group in partnership Worldwide representation including Europe, USA, Japan, China,
More informationVisualization methods for patent data
Visualization methods for patent data Treparel 2013 Dr. Anton Heijs (CTO & Founder) Delft, The Netherlands Introduction Treparel can provide advanced visualizations for patent data. This document describes
More informationUsing Patent Analysis to Supercharge Patent Licensing Programs. Prepared for:
Using Patent Analysis to Supercharge Patent Licensing Programs Prepared for: About AcclaimIP and FPO 10 years experience bringing patent data to millions of users. The AcclaimIP project started in 2010
More informationTIETS34 Seminar: Data Mining on Biometric identification
TIETS34 Seminar: Data Mining on Biometric identification Youming Zhang Computer Science, School of Information Sciences, 33014 University of Tampere, Finland Youming.Zhang@uta.fi Course Description Content
More informationBIG DATA & DATA SCIENCE
BIG DATA & DATA SCIENCE ACADEMY PROGRAMS IN-COMPANY TRAINING PORTFOLIO 2 TRAINING PORTFOLIO 2016 Synergic Academy Solutions BIG DATA FOR LEADING BUSINESS Big data promises a significant shift in the way
More informationService 2 - IPR analysis and survey mini-guide
Service 2 - IPR analysis and survey mini-guide INDEX Page 2 - What IPR information retrieval is? Page 3 - Use of IPR information for your business Page 4 - Use of IPR information to find a business strategy
More informationPredictive analytics for the business analyst: your first steps with SAP InfiniteInsight
Predictive analytics for the business analyst: your first steps with SAP InfiniteInsight Pierpaolo Vezzosi, SAP SESSION CODE: 0605 Summary Who said you need a PhD to do sophisticated predictive analysis?
More informationHow To Make Sense Of Data With Altilia
HOW TO MAKE SENSE OF BIG DATA TO BETTER DRIVE BUSINESS PROCESSES, IMPROVE DECISION-MAKING, AND SUCCESSFULLY COMPETE IN TODAY S MARKETS. ALTILIA turns Big Data into Smart Data and enables businesses to
More informationINTRODUCTION. IoT AND IP STRATEGIES
INTRODUCTION At first, the Internet of Things (IoT) may seem like an idea straight out of science fiction. However, on closer consideration, we realize that the process of connecting everyday electronic
More informationA Hurwitz white paper. Inventing the Future. Judith Hurwitz President and CEO. Sponsored by Hitachi
Judith Hurwitz President and CEO Sponsored by Hitachi Introduction Only a few years ago, the greatest concern for businesses was being able to link traditional IT with the requirements of business units.
More informationDr Victor Zhitomirsky. Patenting in the UK Master Report. www.patanalyse.com/uk_patents. UK Patent Attorneys. 2011 www.patanalyse.
Dr Victor Zhitomirsky Patenting in the UK Master Report www.patanalyse.com/uk_patents UK Patent Attorneys 2011 www.patanalyse.com 2 Introduction PatAnalyse is in the business of delivering IP intelligence
More informationFacilitate Open Science Training for European Research
Facilitate Open Science Training for European Research Addressing IP challenges in collaborations and making data openly accessible Joe Doyle, Intellectual Property Manager, Enterprise Ireland Open access
More informationMachine Learning. Chapter 18, 21. Some material adopted from notes by Chuck Dyer
Machine Learning Chapter 18, 21 Some material adopted from notes by Chuck Dyer What is learning? Learning denotes changes in a system that... enable a system to do the same task more efficiently the next
More informationMachine Learning: Overview
Machine Learning: Overview Why Learning? Learning is a core of property of being intelligent. Hence Machine learning is a core subarea of Artificial Intelligence. There is a need for programs to behave
More informationFight fire with fire when protecting sensitive data
Fight fire with fire when protecting sensitive data White paper by Yaniv Avidan published: January 2016 In an era when both routine and non-routine tasks are automated such as having a diagnostic capsule
More informationData Science & Big Data Practice
INSIGHTS ANALYTICS INNOVATIONS Data Science & Big Data Practice Manufacturing Internet of Things (IoT) Amplify Serviceability and Productivity by integrating machine /sensor data with Data Science What
More informationInternet of Things. Reply Platform
Internet of Things Reply Platform Internet of Things: Concept Reply vision An ecosystem of connected people, objects and services; enabled by pervasive and transparent technology built to improve our quality
More informationCognitive z. Mathew Thoennes IBM Research System z Research June 13, 2016
Cognitive z Mathew Thoennes IBM Research System z Research June 13, 2016 Agenda What is Cognitive? Watson Explorer Overview Demo What is cognitive? Cognitive analytics - A set of technologies and processes
More informationVisionet IT Modernization Empowering Change
Visionet IT Modernization A Visionet Systems White Paper September 2009 Visionet Systems Inc. 3 Cedar Brook Dr. Cranbury, NJ 08512 Tel: 609 360-0501 Table of Contents 1 Executive Summary... 4 2 Introduction...
More informationANALYTICS IN BIG DATA ERA
ANALYTICS IN BIG DATA ERA ANALYTICS TECHNOLOGY AND ARCHITECTURE TO MANAGE VELOCITY AND VARIETY, DISCOVER RELATIONSHIPS AND CLASSIFY HUGE AMOUNT OF DATA MAURIZIO SALUSTI SAS Copyr i g ht 2012, SAS Ins titut
More informationThe Internet of Things and I4.0 is an Evolution. New Markets (e.g. maintenance hub operator) Data Driven. Services. (e.g. predictive.
Industrie 4.0 and Internet of Things July 9, 2015 The Internet of Things and I4.0 is an Evolution Business Impact 40-50% CAGR for M2M market until 2020* IoT Space Data Driven Services (e.g. predictive
More informationManagement Decision Making. Hadi Hosseini CS 330 David R. Cheriton School of Computer Science University of Waterloo July 14, 2011
Management Decision Making Hadi Hosseini CS 330 David R. Cheriton School of Computer Science University of Waterloo July 14, 2011 Management decision making Decision making Spreadsheet exercise Data visualization,
More informationSURVEY REPORT DATA SCIENCE SOCIETY 2014
SURVEY REPORT DATA SCIENCE SOCIETY 2014 TABLE OF CONTENTS Contents About the Initiative 1 Report Summary 2 Participants Info 3 Participants Expertise 6 Suggested Discussion Topics 7 Selected Responses
More informationIntroduction to Data Mining and Machine Learning Techniques. Iza Moise, Evangelos Pournaras, Dirk Helbing
Introduction to Data Mining and Machine Learning Techniques Iza Moise, Evangelos Pournaras, Dirk Helbing Iza Moise, Evangelos Pournaras, Dirk Helbing 1 Overview Main principles of data mining Definition
More informationGfK 2016 Tech Trends 2016
1 Contents 1 2 3 Evolving behavior today s connected consumers Driving you forward 10 tech trends for 2016 Growth from knowledge turning research into smart business decisions 2 Evolving behavior today
More informationDATA MINING TECHNOLOGY. Keywords: data mining, data warehouse, knowledge discovery, OLAP, OLAM.
DATA MINING TECHNOLOGY Georgiana Marin 1 Abstract In terms of data processing, classical statistical models are restrictive; it requires hypotheses, the knowledge and experience of specialists, equations,
More informationA New Era Of Analytic
Penang egovernment Seminar 2014 A New Era Of Analytic Megat Anuar Idris Head, Project Delivery, Business Analytics & Big Data Agenda Overview of Big Data Case Studies on Big Data Big Data Technology Readiness
More informationDynamic Thinking : Patent Search and Analysis
Dynamic Thinking : Patent Search and Analysis About WIPS Worldwide Intellectual Property Service Partnership Authorized Prior Art Search Institute. Authorized Trademark & Design Art Search Institute. Authorized
More informationbig data in the European Statistical System
Conference by STATEC and EUROSTAT Savoir pour agir: la statistique publique au service des citoyens big data in the European Statistical System Michail SKALIOTIS EUROSTAT, Head of Task Force 'Big Data'
More informationPublic Sector Solutions
Public Sector Solutions The New Jersey DOT Command Center uses INRIX real-time data and analytics to monitor congestion and deploy resources proactively to manage traffic flow and inform travelers. INRIX
More informationAndroid Phone Controlled Robot Using Bluetooth
International Journal of Electronic and Electrical Engineering. ISSN 0974-2174, Volume 7, Number 5 (2014), pp. 443-448 International Research Publication House http://www.irphouse.com Android Phone Controlled
More informationWith Bosch Software Innovations ConnectedManufacturing Solutions.
Production Performance Manager How to systematically improve machine availability. www.bosch-si.com/production-performance-manager With Bosch Software Innovations ConnectedManufacturing Solutions. Software
More informationFinding. TECHNOLOGY Using PATENTS. https://patentscope.wipo.int. An Introduction
Finding TECHNOLOGY Using PATENTS An Introduction https://patentscope.wipo.int 2 Patents represent a vast source of information covering every field of technology. Using patent information to find technology
More information10 Essential Google Analytics Reports And How They Matter to B2B Executives
10 Essential Google Analytics Reports And How They Matter to B2B Executives What Are Google Analytics Reports? Google Analytics reports are data collections within the Google Analytics web application
More informationIoT-03-2017 R&I on IoT integration and platforms INTERNET OF THINGS FOCUS AREA
HORIZON 2020 WP 2016-17 IoT-03-2017 R&I on IoT integration and platforms INTERNET OF THINGS DG CONNECT European Commission Internet of Things As enabler of a future hyper-connected society, the Internet
More informationBig Data Text Mining and Visualization. Anton Heijs
Copyright 2007 by Treparel Information Solutions BV. This report nor any part of it may be copied, circulated, quoted without prior written approval from Treparel7 Treparel Information Solutions BV Delftechpark
More informationFact sheet. Tractable. Automating visual recognition tasks with Artificial Intelligence
Fact sheet Tractable Automating visual recognition tasks with Artificial Intelligence Tractable enables computers to see better than humans We develop artificial neural networks capable of recognising
More informationBuilding a Database to Predict Customer Needs
INFORMATION TECHNOLOGY TopicalNet, Inc (formerly Continuum Software, Inc.) Building a Database to Predict Customer Needs Since the early 1990s, organizations have used data warehouses and data-mining tools
More informationMEDICAL DATA MINING. Timothy Hays, PhD. Health IT Strategy Executive Dynamics Research Corporation (DRC) December 13, 2012
MEDICAL DATA MINING Timothy Hays, PhD Health IT Strategy Executive Dynamics Research Corporation (DRC) December 13, 2012 2 Healthcare in America Is a VERY Large Domain with Enormous Opportunities for Data
More informationInternational Journal of Advanced Engineering Research and Applications (IJAERA) ISSN: 2454-2377 Vol. 1, Issue 6, October 2015. Big Data and Hadoop
ISSN: 2454-2377, October 2015 Big Data and Hadoop Simmi Bagga 1 Satinder Kaur 2 1 Assistant Professor, Sant Hira Dass Kanya MahaVidyalaya, Kala Sanghian, Distt Kpt. INDIA E-mail: simmibagga12@gmail.com
More informationAmplify Serviceability and Productivity by integrating machine /sensor data with Data Science
Data Science & Big Data Practice INSIGHTS ANALYTICS INNOVATIONS Manufacturing IoT Amplify Serviceability and Productivity by integrating machine /sensor data with Data Science What is Internet of Things
More informationBig data and its transformational effects
Big data and its transformational effects Professor Fai Cheng Head of Research & Technology September 2015 Working together for a safer world Topics Lloyd s Register Big Data Data driven world Data driven
More informationTrends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum
Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum Siva Ravada Senior Director of Development Oracle Spatial and MapViewer 2 Evolving Technology Platforms
More informationInternet of Things (IoT): A vision, architectural elements, and future directions
SeoulTech UCS Lab 2014-2 st Internet of Things (IoT): A vision, architectural elements, and future directions 2014. 11. 18 Won Min Kang Email: wkaqhsk0@seoultech.ac.kr Table of contents Open challenges
More informationExtend your analytic capabilities with SAP Predictive Analysis
September 9 11, 2013 Anaheim, California Extend your analytic capabilities with SAP Predictive Analysis Charles Gadalla Learning Points Advanced analytics strategy at SAP Simplifying predictive analytics
More informationwww.thevantagepoint.com
Doing More with Less: How efficient analysis can improve your vantage point on information Nils Newman Director of New Business Development Search Technology newman@searchtech.com PIUG Workshop Topics
More informationMSCA 31000 Introduction to Statistical Concepts
MSCA 31000 Introduction to Statistical Concepts This course provides general exposure to basic statistical concepts that are necessary for students to understand the content presented in more advanced
More informationUsing Big Data Analytics
Using Big Data Analytics to find your Competitive Advantage Alexander van Servellen a.vanservellen@elsevier.com 2013 Electronic Resources and Consortia (November 6 th, 2013) The Topic What is Big Data
More informationImproving Decision Making and Managing Knowledge
Improving Decision Making and Managing Knowledge Decision Making and Information Systems Information Requirements of Key Decision-Making Groups in a Firm Senior managers, middle managers, operational managers,
More informationCourse 6234A: Implementing and Maintaining Microsoft SQL Server 2008 Analysis Services
Course 6234A: Implementing and Maintaining Microsoft SQL Server 2008 Analysis Services Length: Delivery Method: 3 Days Instructor-led (classroom) About this Course Elements of this syllabus are subject
More informationKeep Decypha-ing! What s in it for You?
What s in it for You? Decypha is a comprehensive financial platform offering decision-enabling intelligence on the MENA region and even beyond. It has been designed using global best practices for investment
More informationThe Text Analytics Market(s)
The Text Analytics Market(s) Competitive landscape and trends by Curt A. Monash, Ph.D. President, Monash Research Editor, Text Technologies contact@monash.com http://www.monash.com http://www.texttechnologies.com
More informationA Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks
A Systemic Artificial Intelligence (AI) Approach to Difficult Text Analytics Tasks Text Analytics World, Boston, 2013 Lars Hard, CTO Agenda Difficult text analytics tasks Feature extraction Bio-inspired
More informationMultistep Dynamic Expert Sourcing
+33 1 69 33 59 59 MULTISTEP DYNAMIC EXPERT SOURCING 1 A Novel Approach for Open Innovation Platforms Multistep Dynamic Expert Sourcing Albert Meige & Boris Golden August 2010 X- Technologies Ecole Polytechnique
More informationText Mining: The state of the art and the challenges
Text Mining: The state of the art and the challenges Ah-Hwee Tan Kent Ridge Digital Labs 21 Heng Mui Keng Terrace Singapore 119613 Email: ahhwee@krdl.org.sg Abstract Text mining, also known as text data
More informationBig Data: What You Should Know. Mark Child Research Manager - Software IDC CEMA
Big Data: What You Should Know Mark Child Research Manager - Software IDC CEMA Agenda Market Dynamics Defining Big Data Technology Trends Information and Intelligence Market Realities Future Applications
More informationChapter 11. Managing Knowledge
Chapter 11 Managing Knowledge VIDEO CASES Video Case 1: How IBM s Watson Became a Jeopardy Champion. Video Case 2: Tour: Alfresco: Open Source Document Management System Video Case 3: L'Oréal: Knowledge
More informationIntellectual Property Commercialisation
Intellectual Property Commercialisation Building Business on Your Ideas Tralee Institute of Technology 16 th April 2015 Joe Doyle Intellectual Property Manager Enterprise Ireland My objectives: Contextual
More informationWorldwide Advanced and Predictive Analytics Software Market Shares, 2014: The Rise of the Long Tail
MARKET SHARE Worldwide Advanced and Predictive Analytics Software Market Shares, 2014: The Rise of the Long Tail Alys Woodward Dan Vesset IDC MARKET SHARE FIGURE FIGURE 1 Worldwide Advanced and Predictive
More informationMicrosoft Dynamics NAV
Microsoft Dynamics NAV Maximizing value through business insight Business Intelligence White Paper November 2011 The information contained in this document represents the current view of Microsoft Corporation
More informationA CSi Solution for Jack Henry Streamline
A CSi Solution for Jack Henry Streamline Compliance Logic System, or CLS, is software that allows your compliance officer to create unique disclosures based on your institution s products and policies
More informationBig Data: Rethinking Text Visualization
Big Data: Rethinking Text Visualization Dr. Anton Heijs anton.heijs@treparel.com Treparel April 8, 2013 Abstract In this white paper we discuss text visualization approaches and how these are important
More informationAlexander Nikov. 5. Database Systems and Managing Data Resources. Learning Objectives. RR Donnelley Tries to Master Its Data
INFO 1500 Introduction to IT Fundamentals 5. Database Systems and Managing Data Resources Learning Objectives 1. Describe how the problems of managing data resources in a traditional file environment are
More informationBig Data Analytics. Lucas Rego Drumond
Big Data Analytics Lucas Rego Drumond Information Systems and Machine Learning Lab (ISMLL) Institute of Computer Science University of Hildesheim, Germany Big Data Analytics Big Data Analytics 1 / 36 Outline
More informationIBM Cognos TM1 Executive Viewer Fast self-service analytics
Data Sheet IBM Cognos TM1 Executive Viewer Fast self-service analytics Overview IBM Cognos TM1 Executive Viewer provides business users with selfservice, real-time, Web-based access to information from
More informationStaffing for NextGen ITS Operations. Bob Edelstein ITS Practice Leader
Staffing for NextGen ITS Operations Bob Edelstein ITS Practice Leader Overview Traffic Operations Centers Transportation Management Centers TMCs are transforming to be more proactive in addressing recurring
More informationChapter ML:XI. XI. Cluster Analysis
Chapter ML:XI XI. Cluster Analysis Data Mining Overview Cluster Analysis Basics Hierarchical Cluster Analysis Iterative Cluster Analysis Density-Based Cluster Analysis Cluster Evaluation Constrained Cluster
More informationNo BI without Machine Learning
No BI without Machine Learning Francis Pieraut francis@qmining.com http://fraka6.blogspot.com/ 10 March 2011 MTI-820 ETS Too Much Data Supervised Learning (classification) Unsupervised Learning (clustering)
More informationWhat the Hell is Big Data?
Presentation What the Hell is Big Data? Bernard Marr www.ap-institute.com 1 Background 2 Navigating to Success 3 Navigation Today 4 The Global Data Revolution 5 The Intelligent Company Model Strategic
More informationData Validation and Data Management Solutions
FRONTIER TECHNOLOGY, INC. Advanced Technology for Superior Solutions. and Solutions Abstract Within the performance evaluation and calibration communities, test programs are driven by requirements, test
More informationData Isn't Everything
June 17, 2015 Innovate Forward Data Isn't Everything The Challenges of Big Data, Advanced Analytics, and Advance Computation Devices for Transportation Agencies. Using Data to Support Mission, Administration,
More informationINTRODUCTION TO DATA MINING SAS ENTERPRISE MINER
INTRODUCTION TO DATA MINING SAS ENTERPRISE MINER Mary-Elizabeth ( M-E ) Eddlestone Principal Systems Engineer, Analytics SAS Customer Loyalty, SAS Institute, Inc. AGENDA Overview/Introduction to Data Mining
More informationredesigning the data landscape to deliver true business intelligence Your business technologists. Powering progress
redesigning the data landscape to deliver true business intelligence Your business technologists. Powering progress The changing face of data complexity The storage, retrieval and management of data has
More informationArtificial Intelligence and Testing. Kishore Durg AccentureTechnology June 2016
Artificial Intelligence and Testing Kishore Durg AccentureTechnology June 2016 Copyright 2016 Accenture Technology Lab (Bangalore). All rights reserved. 1 Intelligent automation: The essential co-worker
More informationOpen source framework for data-flow visual analytic tools for large databases
Open source framework for data-flow visual analytic tools for large databases D5.6 v1.0 WP5 Visual Analytics: D5.6 Open source framework for data flow visual analytic tools for large databases Dissemination
More informationThe Purview Solution Integration With Splunk
The Purview Solution Integration With Splunk Integrating Application Management and Business Analytics With Other IT Management Systems A SOLUTION WHITE PAPER WHITE PAPER Introduction Purview Integration
More informationDTU 2010 Patent Course
The great questions DTU 2010 Patent Course Ideas & Innovation DanishTechnological Institute www.opfind.nu Rasmus B. Offersen, licensing consultant tel. 72 20 27 62 Is your idea novel Can it be protected
More informationDATA WAREHOUSE AND DATA MINING NECCESSITY OR USELESS INVESTMENT
Scientific Bulletin Economic Sciences, Vol. 9 (15) - Information technology - DATA WAREHOUSE AND DATA MINING NECCESSITY OR USELESS INVESTMENT Associate Professor, Ph.D. Emil BURTESCU University of Pitesti,
More informationTHOMSON REUTERS CORTELLIS FOR INFORMATICS. REUTERS/ Aly Song
THOMSON REUTERS CORTELLIS FOR INFORMATICS REUTERS/ Aly Song THOMSON REUTERS CORTELLIS FOR INFORMATICS 1 Table of Contents Table of Contents...1 The challenge... 2 The solution... 2 WHAT CAN YOU DO WITH
More informationDATAMEER WHITE PAPER. Beyond BI. Big Data Analytic Use Cases
DATAMEER WHITE PAPER Beyond BI Big Data Analytic Use Cases This white paper discusses the types and characteristics of big data analytics use cases, how they differ from traditional business intelligence
More informationAV-24 Advanced Analytics for Predictive Maintenance
Slide 1 AV-24 Advanced Analytics for Predictive Maintenance Big Data Meets Equipment Reliability and Maintenance Paul Sheremeto President & CEO Pattern Discovery Technologies Inc. social.invensys.com @InvensysOpsMgmt
More informationChallenges and Opportunities in Data Mining: Personalization
Challenges and Opportunities in Data Mining: Big Data, Predictive User Modeling, and Personalization Bamshad Mobasher School of Computing DePaul University, April 20, 2012 Google Trends: Data Mining vs.
More informationA Statistical Text Mining Method for Patent Analysis
A Statistical Text Mining Method for Patent Analysis Department of Statistics Cheongju University, shjun@cju.ac.kr Abstract Most text data from diverse document databases are unsuitable for analytical
More informationSelf-Improving Supply Chains
Self-Improving Supply Chains Cyrus Hadavi Ph.D. Adexa, Inc. All Rights Reserved January 4, 2016 Self-Improving Supply Chains Imagine a world where supply chain planning systems can mold themselves into
More informationHi, we re. October 2015 Investor Presentation
Hi, we re October 2015 Investor Presentation Disclaimer THIS PRESENTATION IS NOT A PROSPECTUS NOR AN OFFER FOR SECURITIES IN ANY JURISDICTION NOR A SECURITIES RECOMMENDATION. THE INFORMATION IN THIS PRESENTATION
More informationDolcera Software and Services. Enhance your business Potential
Dolcera Software and Services Enhance your business Potential About Dolcera Dolcera is a Knowledge Services company based out of Silicon Valley, USA and Hyderabad, India Dolcera s clients include dozens
More informationGain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora
SAP Brief SAP Technology SAP HANA Vora Objectives Gain Contextual Awareness for a Smarter Digital Enterprise with SAP HANA Vora Bridge the divide between enterprise data and Big Data Bridge the divide
More informationUnlocking the Intelligence in. Big Data. Ron Kasabian General Manager Big Data Solutions Intel Corporation
Unlocking the Intelligence in Big Data Ron Kasabian General Manager Big Data Solutions Intel Corporation Volume & Type of Data What s Driving Big Data? 10X Data growth by 2016 90% unstructured 1 Lower
More informationDansk IT Big Data i de største danske banker
Dansk IT Big Data i de største danske banker How can we realize the benefits Presentation 7/4-2016 Jens Chr. Ipsen, head of Information Management & Data Warehouse The essence of Danske Bank Vision To
More informationSearch and Data Mining: Techniques. Introduction Anna Yarygina Boris Novikov
Search and Data Mining: Techniques Introduction Anna Yarygina Boris Novikov Data Analytics: Conference Sections Fundamentals for data analytics Mechanisms and features Big Data Huge data Target analytics
More informationAutomatic Document Categorization A Hummingbird White Paper
Automatic Document Categorization A Hummingbird White Paper Automatic Document Categorization While every attempt has been made to ensure the accuracy and completeness of the information in this document,
More informationTutkimustulosten kaupallistaminen ja Proof of Concept 1.12.2015 Matti Saarinen, CEO Helmee Imaging Oy
Tutkimustulosten kaupallistaminen ja Proof of Concept 1.12.2015 Matti Saarinen, CEO Helmee Imaging Oy 2 Helmee Imaging Ltd. Head quarters in Tampere, Finland Originally a Spin-off from VTT National Research
More informationAdvanced analytics at your hands
2.3 Advanced analytics at your hands Neural Designer is the most powerful predictive analytics software. It uses innovative neural networks techniques to provide data scientists with results in a way previously
More informationWhy big data? Lessons from a Decade+ Experiment in Big Data
Why big data? Lessons from a Decade+ Experiment in Big Data David Belanger PhD Senior Research Fellow Stevens Institute of Technology dbelange@stevens.edu 1 What Does Big Look Like? 7 Image Source Page:
More informationFrom Lawful to Massive Interception : Aggregation of sources. amesys - Prague ISS World Europe 2008
From Lawful to Massive Interception : Aggregation of sources Agenda! Introduction! amesys Company! Lawful vs Massive! A centralized point of view! Range of Products! Conclusion Objectives! Increasing need
More informationORBIT IP BUSINESS INTELLIGENCE Product Presentation
ORBIT IP BUSINESS INTELLIGENCE Product Presentation IP BUSINESS INTELLIGENCE WORKFLOW LANDSCAPE TECHNOLOGY SCOUTING AUDIT MONETIZATION ANALYZE THE IP Business Intelligence 3 Search: Topic of study Define
More informationMSCA 31000 Introduction to Statistical Concepts
MSCA 31000 Introduction to Statistical Concepts This course provides general exposure to basic statistical concepts that are necessary for students to understand the content presented in more advanced
More informationBusiness Intelligence services
Business Intelligence services 2013 Benefit from ScienceSoft BI expertise By offering analytic tool development & support, on-demand reporting and comprehensive data analysis, ScienceSoft helps its Customers
More informationBig Data og Smart City. Knut H. H. Johansen CEO esmart System 7. mai 2015
Big Data og Smart City Knut H. H. Johansen CEO esmart System 7. mai 2015 2 Smart Cities Big Data & Analytics Integrated Operations Smart City? No one definition for smart city > depends smartness comes
More information