The document discusses the cognitive era and capabilities of cognitive systems like IBM Watson. It provides an overview of Findwise, a consulting firm that specializes in search and analytics. Findwise has built Swedish language support for IBM Watson Explorer and provides text analytics services to help clients understand customer feedback and improve products. Their approach combines structured and unstructured information for fact-based decision making.
Findability Day 2016 - Enterprise Search and Findability Survey 2016Findwise
In April 2016, Findwise opened the fifth annual Enterprise Search and Findability Survey to investigate how search is managed and used globally. Mattias Ellison presents some of the most interesting founds at Findability Day 2016 in Stockholm.
Scania interim report january september 2016Scania Group
Scania’s sales reached SEK 75.2 billion in the first nine months of 2016 and the company’s underlying operational performance was strong. Higher vehicle volume in Europe and increased service revenue was partly offset by negative currency rate effects and lower deliveries in Latin America.
https://www.excelautomationinc.com : Rotex is one of the most trusted names in the Cables and pipe transits for marine applications and Excel Automation of Brunswick, Ohio is the authorized distributor of all Rotex parts here. So if you are looking for cable entry solutions of EMC sealing systems, pipe entry solutions, cable and pipe management systems, your search ends at Excel Automation.
The 2017 Accenture Technology Vision report showcases the top five disruptive IT trends and innovations shaping the business landscape in 2017 and beyond. Take action today and shape technology to fit your needs.
Learn more at www.accenture.com/technologyvision
Findability Day 2016 - Enterprise Search and Findability Survey 2016Findwise
In April 2016, Findwise opened the fifth annual Enterprise Search and Findability Survey to investigate how search is managed and used globally. Mattias Ellison presents some of the most interesting founds at Findability Day 2016 in Stockholm.
Scania interim report january september 2016Scania Group
Scania’s sales reached SEK 75.2 billion in the first nine months of 2016 and the company’s underlying operational performance was strong. Higher vehicle volume in Europe and increased service revenue was partly offset by negative currency rate effects and lower deliveries in Latin America.
https://www.excelautomationinc.com : Rotex is one of the most trusted names in the Cables and pipe transits for marine applications and Excel Automation of Brunswick, Ohio is the authorized distributor of all Rotex parts here. So if you are looking for cable entry solutions of EMC sealing systems, pipe entry solutions, cable and pipe management systems, your search ends at Excel Automation.
The 2017 Accenture Technology Vision report showcases the top five disruptive IT trends and innovations shaping the business landscape in 2017 and beyond. Take action today and shape technology to fit your needs.
Learn more at www.accenture.com/technologyvision
How is Watson Changing the Future of the Automative Industry?IBM Watson
“How is Watson Changing the Future of the Automotive Industry?” presented in Livonia, MI. Event participants were introduced to the age of cognitive computing, where cognitive analytics evaluate complex data in new ways to help solve the industry's most challenging problems. Cognitive computing has arrived, and its potential to transform the industry is momentous. Learn how cognitive solutions are being applied in the automotive industry and how industry leaders are embracing this ground breaking technology to spark the digital future.
Post 1What is text analytics How does it differ from text mini.docxstilliegeorgiana
Post 1:
What is text analytics? How does it differ from text mining?
Text Analytics is applying of statistical and machine learning techniques to be able to predict /prescribe or infer any information from the text-mined data. Text mining is a tool that helps in getting the data cleaned up.Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
Differences between Text Mining and Text Analytics:
• Text Mining and Text Analytics solve the same problems, but use different techniques and are complementary ways to automatically extract meaning from text.
• Text Analytics is developed within the field of computational linguistics. It has the ability to encode human understanding into a series of linguistic rules which are generated by humans are high in precision, but they do not automatically adapt and are usually fragile when tried in new situations.
• Text mining is a newer discipline arising out of the fields of statistics, data mining, and machine learning. Its strength is the ability to inductively create models from collections of historical data. Because statistical models are learned from training data they are adaptive and can identify “unknown unknowns”, leading to the better recall. Still, they can be prone to missing something that would seem obvious to a human.
• Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
• Due to their different perspectives and strengths, combining text analytics with text mining often leads to better performance than either approach alone.
2. What technologies were used in building Watson (both hardware and software)?
Watson is an extraordinary computer system (a novel combination of advanced hardware an software) designed at answering questions posed in natural human language.Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM's first CEO and industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.
Watson received the first prize of $1 million.The goal was to advance computer science by exploring new ways for computer technology to affect science, business, and society.IBM undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV quiz show Jeopardy!The extent of the challenge in ...
Post 1What is text analytics How does it differ from text minianhcrowley
Post 1:
What is text analytics? How does it differ from text mining?
Text Analytics is applying of statistical and machine learning techniques to be able to predict /prescribe or infer any information from the text-mined data. Text mining is a tool that helps in getting the data cleaned up.Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
Differences between Text Mining and Text Analytics:
• Text Mining and Text Analytics solve the same problems, but use different techniques and are complementary ways to automatically extract meaning from text.
• Text Analytics is developed within the field of computational linguistics. It has the ability to encode human understanding into a series of linguistic rules which are generated by humans are high in precision, but they do not automatically adapt and are usually fragile when tried in new situations.
• Text mining is a newer discipline arising out of the fields of statistics, data mining, and machine learning. Its strength is the ability to inductively create models from collections of historical data. Because statistical models are learned from training data they are adaptive and can identify “unknown unknowns”, leading to the better recall. Still, they can be prone to missing something that would seem obvious to a human.
• Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
• Due to their different perspectives and strengths, combining text analytics with text mining often leads to better performance than either approach alone.
2. What technologies were used in building Watson (both hardware and software)?
Watson is an extraordinary computer system (a novel combination of advanced hardware an software) designed at answering questions posed in natural human language.Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM's first CEO and industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.
Watson received the first prize of $1 million.The goal was to advance computer science by exploring new ways for computer technology to affect science, business, and society.IBM undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV quiz show Jeopardy!The extent of the challenge in ...
In this lecture we explore how big datasets can be used with the Weka workbench and what other issues are currently under discussion in the real world, for ex: big data applications, predictive linguistic analysis, new platforms and new programming languages.
synUosa is a start-up that operate in the Big Data Analysis Business.
synUosa is an independent BU of ArteficeGroup, The BrandLanguageDesign® Company, operating in the Marketing & Communication Biz.
Demystifying IBM Watson: Uncover the Power of Cognitive SolutionsPerficient, Inc.
Successful organizations recognize that information is a strategic asset, capable of strengthening decision making, improving efficiency, reducing risk, and enhancing customer relationships. With the tremendous surge in the volume and diversity of data, leveraging this information across the entire enterprise is a business imperative that cannot be ignored.
IBM Watson harnesses the power of cognitive exploration, machine learning, and natural language processing to answer your most pressing questions, strengthen decision making, scale expertise, uncover key information in unstructured data, and reveal previously undiscovered data patterns and relationships.
In this SlideShare, we discuss:
Trends in cognitive solutions
Use cases for IBM Watson
Real-world Watson success stories
Getting started on the path to cognitive solutions
Discover the evolving technology of artificial intelligence and text analysis. Learn about the importance, types, applications and challenges of the industry. Visit https://www.bytesview.com/ for more information.
Customers express their opinions in complex ways for businesses. From analyzing user reviews to enhancing the businesses, Sentiment analysis plays a significant role.
Watson Customer Engagement offerings deliver a broad range of capabilities for marketing, commerce and supply chain activities. Each offering is designed to complement the skills of forward-thinking professionals like you. To enhance your expertise. To empower you to make better, more informed decisions. And help you take action confidently as you drive your organization's growth and deliver rapid innovation.
When to use the different text analytics tools - Meaning CloudMeaningCloud
Classification, topic extraction, clustering... When to use the different Text Analytics tools?
How to leverage Text Analytics technology for your business
MeaningCloud webinar, February 8th, 2017
More information and recording of the webinar https://www.meaningcloud.com/blog/recorded-webinar-use-different-text-analytics-tools
www.meaningcloud.com
How is Watson Changing the Future of the Automative Industry?IBM Watson
“How is Watson Changing the Future of the Automotive Industry?” presented in Livonia, MI. Event participants were introduced to the age of cognitive computing, where cognitive analytics evaluate complex data in new ways to help solve the industry's most challenging problems. Cognitive computing has arrived, and its potential to transform the industry is momentous. Learn how cognitive solutions are being applied in the automotive industry and how industry leaders are embracing this ground breaking technology to spark the digital future.
Post 1What is text analytics How does it differ from text mini.docxstilliegeorgiana
Post 1:
What is text analytics? How does it differ from text mining?
Text Analytics is applying of statistical and machine learning techniques to be able to predict /prescribe or infer any information from the text-mined data. Text mining is a tool that helps in getting the data cleaned up.Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
Differences between Text Mining and Text Analytics:
• Text Mining and Text Analytics solve the same problems, but use different techniques and are complementary ways to automatically extract meaning from text.
• Text Analytics is developed within the field of computational linguistics. It has the ability to encode human understanding into a series of linguistic rules which are generated by humans are high in precision, but they do not automatically adapt and are usually fragile when tried in new situations.
• Text mining is a newer discipline arising out of the fields of statistics, data mining, and machine learning. Its strength is the ability to inductively create models from collections of historical data. Because statistical models are learned from training data they are adaptive and can identify “unknown unknowns”, leading to the better recall. Still, they can be prone to missing something that would seem obvious to a human.
• Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
• Due to their different perspectives and strengths, combining text analytics with text mining often leads to better performance than either approach alone.
2. What technologies were used in building Watson (both hardware and software)?
Watson is an extraordinary computer system (a novel combination of advanced hardware an software) designed at answering questions posed in natural human language.Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM's first CEO and industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.
Watson received the first prize of $1 million.The goal was to advance computer science by exploring new ways for computer technology to affect science, business, and society.IBM undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV quiz show Jeopardy!The extent of the challenge in ...
Post 1What is text analytics How does it differ from text minianhcrowley
Post 1:
What is text analytics? How does it differ from text mining?
Text Analytics is applying of statistical and machine learning techniques to be able to predict /prescribe or infer any information from the text-mined data. Text mining is a tool that helps in getting the data cleaned up.Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
Differences between Text Mining and Text Analytics:
• Text Mining and Text Analytics solve the same problems, but use different techniques and are complementary ways to automatically extract meaning from text.
• Text Analytics is developed within the field of computational linguistics. It has the ability to encode human understanding into a series of linguistic rules which are generated by humans are high in precision, but they do not automatically adapt and are usually fragile when tried in new situations.
• Text mining is a newer discipline arising out of the fields of statistics, data mining, and machine learning. Its strength is the ability to inductively create models from collections of historical data. Because statistical models are learned from training data they are adaptive and can identify “unknown unknowns”, leading to the better recall. Still, they can be prone to missing something that would seem obvious to a human.
• Text analytics and text mining approaches have essentially equivalent performance. Text analytics requires an expert linguist to produce complex rule sets, whereas text mining requires the analyst to hand-label cases with outcomes or classes to create training data.
• Due to their different perspectives and strengths, combining text analytics with text mining often leads to better performance than either approach alone.
2. What technologies were used in building Watson (both hardware and software)?
Watson is an extraordinary computer system (a novel combination of advanced hardware an software) designed at answering questions posed in natural human language.Watson is an artificially intelligent computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM's first CEO and industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! In 2011, Watson competed on Jeopardy! against former winners Brad Rutter and Ken Jennings.
Watson received the first prize of $1 million.The goal was to advance computer science by exploring new ways for computer technology to affect science, business, and society.IBM undertook a challenge to build a computer system that could compete at the human champion level in real time on the American TV quiz show Jeopardy!The extent of the challenge in ...
In this lecture we explore how big datasets can be used with the Weka workbench and what other issues are currently under discussion in the real world, for ex: big data applications, predictive linguistic analysis, new platforms and new programming languages.
synUosa is a start-up that operate in the Big Data Analysis Business.
synUosa is an independent BU of ArteficeGroup, The BrandLanguageDesign® Company, operating in the Marketing & Communication Biz.
Demystifying IBM Watson: Uncover the Power of Cognitive SolutionsPerficient, Inc.
Successful organizations recognize that information is a strategic asset, capable of strengthening decision making, improving efficiency, reducing risk, and enhancing customer relationships. With the tremendous surge in the volume and diversity of data, leveraging this information across the entire enterprise is a business imperative that cannot be ignored.
IBM Watson harnesses the power of cognitive exploration, machine learning, and natural language processing to answer your most pressing questions, strengthen decision making, scale expertise, uncover key information in unstructured data, and reveal previously undiscovered data patterns and relationships.
In this SlideShare, we discuss:
Trends in cognitive solutions
Use cases for IBM Watson
Real-world Watson success stories
Getting started on the path to cognitive solutions
Discover the evolving technology of artificial intelligence and text analysis. Learn about the importance, types, applications and challenges of the industry. Visit https://www.bytesview.com/ for more information.
Customers express their opinions in complex ways for businesses. From analyzing user reviews to enhancing the businesses, Sentiment analysis plays a significant role.
Watson Customer Engagement offerings deliver a broad range of capabilities for marketing, commerce and supply chain activities. Each offering is designed to complement the skills of forward-thinking professionals like you. To enhance your expertise. To empower you to make better, more informed decisions. And help you take action confidently as you drive your organization's growth and deliver rapid innovation.
When to use the different text analytics tools - Meaning CloudMeaningCloud
Classification, topic extraction, clustering... When to use the different Text Analytics tools?
How to leverage Text Analytics technology for your business
MeaningCloud webinar, February 8th, 2017
More information and recording of the webinar https://www.meaningcloud.com/blog/recorded-webinar-use-different-text-analytics-tools
www.meaningcloud.com
Findability Day 2016 - Enterprise Search and Findability Survey 2016Findwise
In April 2016, Findwise opened the fifth annual Enterprise Search and Findability Survey to investigate how search is managed and used globally. Mattias Ellison presents some of the most interesting founds at Findability Day 2016 in Stockholm.
Elastic presents how The Guardian uses log analysis when creating articles and content on their website.
Findwise talks about Big Data and log analysis and the possibilities it gives.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
7. Hum ans excel at :
Dilemmas
Compassion
Dreaming
Abstraction
Imagination
Morals
Generalization
Cogni t ive Syst em s
excel at :
Common Sense
Natural Language
Locating Knowledge
Pattern Identification
Machine Learning
Eliminate Bias
Endless Capacity
Cognitive systems forge a new partnership
between man and machine.
8. Retrieve and Rank
1
0
Entity Extraction
Sentiment Analysis
Emotion Analysis (Beta)
Keyword Extraction
Concept Tagging
Taxonomy Classification
Author Extraction
Language Detection
Text Extraction
Microformats Parsing
Feed Detection
Linked Data Support
Concept Expansion
Concept Insights
Dialog
Document Conversion
Language Translation
Natural Language Classifier
Personality insights
Relationship Extraction
Retrieve and Rank
Tone Analyzer
Emotive Speech to Text
Text to Speech
Face Detection
Image Link Extraction
Image Tagging
Text Detection
Visual Insights
Visual Recognition
AlchemyData News
Tradeoff Analytics
50 underlying technologies
Watson cognitive capabilities.
Natural Language Classifier
Tone Analyzer
9. SWEDISH LANGUAGE SUPPORT
• Findwise have built Swedish language support for IBM Watson
Explorer in 2012
• The primary component is a PoS (Part-of-Speech) tagger, which can
identify and disambiguate the class to which words belong.
• Other capabilities include sentiment analysis
10. 12
“How can I identify product
failures or failure patterns?”
“How can I improve call
center training and call
handling?”
“How do I know what my
customers want?”
“How do I know what
my customers are
saying about me?”
“How can I improve my products
and services?”
“How can I decipher
customer complaints?”
“How can I
understand why my
customer satisfaction
is decreasing?”
The Need
VOICE OF THE CUSTOMER
11. 13
COMBINING STRUCTURED & UNSTRUCTURED
INFORMATION FOR FACT-BASED DECISIONS
Unstructured informationStructured information
12. Text Analytics is the basis for Customer Feedback Analytics
14
What is Text Analytics?
Text Analytics (NLP*) describes a set of
linguistic, statistical, and machine
learning techniques that allow text to
be analyzed and key information
extraction for business integration
What is Content Analytics?
Content Analytics (Text Analytics + Mining)
refers to the text analytics process plus the
ability to visually identify and explore trends,
patterns, and statistically relevant facts found
in various types of content spread across
internal and external content sources
* Natural Language Processing
EC 4.0 Cu. Ft.
26-Cycle King-Size
Washer – White. I hate
this machine. Have had
3 calls on machine. You
can't wash large items,
Wont' clean in the
middle. Leaves dry
spots through the
clothes, I can only do
1/2 basket of clothes.
Will not clean or mix
bleach in with the
water.....
13. Watson Explorer 16
ANALYZE UNSTRUCTURED
CONTENT WITH CONTENT
MINER
Documents Facets Time Series Deviations Trends
Facet Pairs Dashboard SentimentConnections Reports
Watson Explorer Advanced Edition
14. A concept solution for
security and intelligence
using Watson Explorer
to extract entities and
relationships that is
loaded into IBM i2.
2017-03-27 17
TEXT ANALYTICS AS A SERVICE
CLIENT: SWEDISH ARMED FORCES
16. FINDWISE COMPETENCE
◌ IBM Watson Explorer technicians / developers
◌ Business analysts
◌ Data scientists
◌ Computational linguistics, information retrieval
◌ User experience and front-end developer
◌ Information management consultants
◌ GDPR expertise
17. FOR MORE INFORMATION ABOUT FINDWISE AND
IBM WATSON VISIT:
HTTPS://FINDWISE.COM/TECHNOLOGY/IBM-WATSON-EXPLORER