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Industrial Ontologies Group: our history and team

Industrial Ontologies Group: our history and team

Industrial Ontologies Group: our history and team Vagan Terziyan, Group Leader Industrial Ontologies Group Agora Center, University of Jyväskylä Our History “Industrial Ontologies” Group: Our History

By emily
(312 views)

The role of the knowledge engineer. Knowledge acquisition.

The role of the knowledge engineer. Knowledge acquisition.

The role of the knowledge engineer. Knowledge acquisition. Software development: conventional systems and KBS. You are probably familiar with a standard model of the software development life cycle. It is likely to be something like this: Feasibility study ® Analysis

By zena
(179 views)

IMAT3406 Fuzzy Logic and Knowledge Based Systems (AI)

IMAT3406 Fuzzy Logic and Knowledge Based Systems (AI)

IMAT3406 Fuzzy Logic and Knowledge Based Systems (AI). Introduction to Knowledge Based Systems ( KBS). Most of the KBS notes kindly provided by Dr. Aladdin Ayesh. Lecture Plan for Knowledge Based System. Reading List Not compulsory, but complementary. Knowledge Based Systems

By tivona
(310 views)

Types of Systems; CASE tools

Types of Systems; CASE tools

Types of Systems; CASE tools. Class 3. Why study SA&D?. “meat” of the IS function Winchester house example Art vs. Science Methodologies Comprehensive, multiple-step approaches to systems development Models Representation of system, organization, etc. Techniques

By wilona
(263 views)

Discovery of Patterns in Digital Records

Discovery of Patterns in Digital Records

Discovery of Patterns in Digital Records. DESI III at ICAIL 2009 Global E-Discovery/E-Disclosure Workshop: A Pre-Conference Workshop at the 12th International Conference on Artificial Intelligence and Law A. Shelly Spearing (shellys@lanl.gov) Jorge H. Román (jhr@lanl.gov)

By gittel
(110 views)

Ramtin Raji Kermani, Mehrdad Rashidi, Hadi Yaghoobian

Ramtin Raji Kermani, Mehrdad Rashidi, Hadi Yaghoobian

Uncertainty in Artificial Intelligence. Ramtin Raji Kermani, Mehrdad Rashidi, Hadi Yaghoobian. Overview. Uncertainty Probability Syntax and Semantics Inference Independence and Bayes' Rule. sensors. ?. environment. ?. ?. agent. ?. actuators. model. Uncertain Agent.

By fleur
(171 views)

Efficiency Programming for the (Productive) Masses

Efficiency Programming for the (Productive) Masses

Efficiency Programming for the (Productive) Masses. Armando Fox , Bryan Catanzaro, Shoaib Kamil, Yunsup Lee, Ben Carpenter, Erin Carson, Krste Asanovic, Dave Patterson, Kurt Keutzer UC Berkeley Parallel Computing Lab/UPCRC.

By ady
(176 views)

A Human-Computer Collaboration Approach to Improve Accuracy of an Automated English Scoring System

A Human-Computer Collaboration Approach to Improve Accuracy of an Automated English Scoring System

A Human-Computer Collaboration Approach to Improve Accuracy of an Automated English Scoring System. NAACL-HLT 2010 June 5, 2010 Jee Eun Kim (HUFS) & Kong Joo Lee (CNU ). Outline. Overview of the system Issue Redundant errors Solution Introducing method to determine redundant errors

By ayala
(103 views)

Data Integration: A Status Report

Data Integration: A Status Report

Data Integration: A Status Report. Alon Halevy University of Washington, Seattle BTW 2003. Data Integration Report. Recent progress Mediation languages Query processing (XML and other) Commercial Current challenges Flexible architectures: peer-data mgmt.

By edward
(121 views)

Agent Mediated Electronic Commerce

Agent Mediated Electronic Commerce

Dr. Chris Preist HP Labs. Agent Mediated Electronic Commerce. The Three Phases of Electronic Commerce. Electronic Data Interchange Electronic Marketplaces Agent-Mediated Electronic Commerce. Electronic Data Interchange (EDI).

By durin
(156 views)

Data Mining for Malware Detection Lecture #2 May 27, 2011

Data Mining for Malware Detection Lecture #2 May 27, 2011

Data Mining for Malware Detection Lecture #2 May 27, 2011. Dr. Bhavani Thuraisingham The University of Texas at Dallas. Information Harvesting. Knowledge Mining. Data Mining. Knowledge Discovery in Databases. Data Dredging. Data Archaeology. Data Pattern Processing. Database Mining.

By yates
(2 views)

Machine Learning & Data Mining

Machine Learning & Data Mining

Machine Learning & Data Mining. What is Machine Learning?. a branch of artificial intelligence, concerns the construction and study of systems that can learn from data .

By marsha
(171 views)

Knowledge-based systems

Knowledge-based systems

Knowledge-based systems. Rozália Lakner University of Veszprém Department of Computer Science. An overview. Knowledge-based systems, expert systems structure, characteristics main components advantages, disadvantages Base techniques of knowledge-based systems rule-based techniques

By khuyen
(298 views)

Decision Models and Intelligent Systems

Decision Models and Intelligent Systems

Decision Models and Intelligent Systems. Introduction to Managerial Support Systems. Learning Objectives. Describe managerial roles and understand why they require computerized support for decision making

By babu
(122 views)

‘Visual’ and ‘Metric 3D’

‘Visual’ and ‘Metric 3D’

‘Visual’ and ‘Metric 3D’. Seeing the Invisible and Measuring the Immeasurable with “Software Lenses” Sabine K McNeill. Sickle cells (anaemia) . Seeing more about cells and their environment applies to sickle cells, stem cells and red and white blood cells as examples.

By arawn
(112 views)

INTELLIGENT INFORMATION SYSTEMS

INTELLIGENT INFORMATION SYSTEMS

MIS. CHAPTER 13. INTELLIGENT INFORMATION SYSTEMS. Att and future. Hossein BIDGOLI. Chapter 13 Intelligent Information Systems. l e a r n i n g o u t c o m e s. LO1 Define artificial intelligence and explain how these technologies support decision making.

By etoile
(175 views)

Centro per la Ricerca Scientifica e Tecnologica

Centro per la Ricerca Scientifica e Tecnologica

Centro per la Ricerca Scientifica e Tecnologica. Spoken language technologies: recent advances and future challenges Gianni Lazzari VIENNA July 26. SUMMARY Short introduction on SLT Where are we today ? TC-STAR and RAI projects Outlook for the future.

By wayne
(123 views)

Twittering about #MIC09

Twittering about #MIC09

Twittering about #MIC09. David Wicks Seattle Pacific University. Overview. Participants Why use twitter? How do I tweet? How should I participate? Extramission Presenters How should I prepare tweeters for my session? How should I respond to tweeting during my session?

By keiji
(110 views)

Social Search

Social Search

2011-05-11. Chapter 10. Social Search. Borim Ryu. Contents. What Is Social Search?. Ⅰ. User Tags and Manual Indexing. Ⅱ. Searching with Communities. Ⅲ. Filtering and Recommending. Ⅳ. Peer-to-Peer and Metasearch. Ⅴ. 10.1 What Is Social Search?. Social search Definitions:

By lavender
(161 views)

Introduction to MIS

Introduction to MIS

Introduction to MIS. Chapter 9 Complex Decisions and Artificial Intelligence. Complex Decisions & Artificial Intelligence. Strategy. Decision. Computer analysis of data and model. Neural network. Tactics. Operations. Company. Outline. Specialized Problems Expert Systems DSS and ES

By rimona
(74 views)

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