Department of Informatics, Nicolaus Copernicus University, Toruń

Slides:



Advertisements
Similar presentations
Computational Intelligence: Methods and Applications Lecture 1 Organization and overview Włodzisław Duch Dept. of Informatics, UMK Google: W Duch.
Advertisements

GhostMiner Wine example Włodzisław Duch Dept. of Informatics, Nicholas Copernicus University, Toruń, Poland ISEP Porto,
Heterogeneous Forests of Decision Trees Krzysztof Grąbczewski & Włodzisław Duch Department of Informatics, Nicholas Copernicus University, Torun, Poland.
Department of Mathematics and Computer Science
Heterogeneous adaptive systems Włodzisław Duch & Krzysztof Grąbczewski Department of Informatics, Nicholas Copernicus University, Torun, Poland.
K-separability Włodzisław Duch Department of Informatics Nicolaus Copernicus University, Torun, Poland School of Computer Engineering, Nanyang Technological.
Fuzzy rule-based system derived from similarity to prototypes Włodzisław Duch Department of Informatics, Nicolaus Copernicus University, Poland School.
Transfer functions: hidden possibilities for better neural networks. Włodzisław Duch and Norbert Jankowski Department of Computer Methods, Nicholas Copernicus.
Artificial Intelligence and Lisp Lecture 13 Additional Topics in Artificial Intelligence LiU Course TDDC65 Autumn Semester, 2010
Intelligent Agent Systems. Artificial Intelligence Systems that think like humans Systems that think rationally Systems that act like humans Systems that.
Minimum Spanning Trees Displaying Semantic Similarity Włodzisław Duch & Paweł Matykiewicz Department of Informatics, UMK Toruń School of Computer Engineering,
Foundations of Computational Intelligence The basis of Smart Adaptive Systems of the future? Bogdan Gabrys Smart Technology Research Centre Computational.
Review 4 Chapters 8, 9, 10.
Learning Programs Danielle and Joseph Bennett (and Lorelei) 4 December 2007.
02 -1 Lecture 02 Agent Technology Topics –Introduction –Agent Reasoning –Agent Learning –Ontology Engineering –User Modeling –Mobile Agents –Multi-Agent.
Feature selection based on information theory, consistency and separability indices Włodzisław Duch, Tomasz Winiarski, Krzysztof Grąbczewski, Jacek Biesiada,
Cognitive Modeling & Information Processing Metaphor.
Presented To: Madam Nadia Gul Presented By: Bi Bi Mariam.
Introduction to Data Mining Engineering Group in ACL.
9/30/2004TCSS588A Isabelle Bichindaritz1 Introduction to Bioinformatics.
Introduction to Computer and Programming CS-101 Lecture 6 By : Lecturer : Omer Salih Dawood Department of Computer Science College of Arts and Science.
Formal Empirical Applied Mathematical and technical methods and theories Cognitive, behavioral, and organizational techniques and theories ImagingBioInformaticsClinical.
C OMPUTER S CIENCE, C OMPUTER E NGINEERING, I NFORMATION T ECHNOLOGY AND S YSTEMS, F LOW OF C ONTROL, B ATCH AND I NTERACTIVE P ROCESSING Week 5 Mr. Mohammed.
Department of Information Technology Indian Institute of Information Technology and Management Gwalior AASF hIQ 1 st Nov ‘09 Department of Information.
Understanding Human Nature: Confluence of Humans with Computers Włodzisław Duch Department of Informatics, Nicolaus Copernicus University, Toruń, Poland.
Structure of Study Programmes Bachelor of Computer Science Bachelor of Information Technology Master of Computer Science Master of Information Technology.
Self organizing maps 1 iCSC2014, Juan López González, University of Oviedo Self organizing maps A visualization technique with data dimension reduction.
IJCNN 2012 Competition: Classification of Psychiatric Problems Based on Saccades Włodzisław Duch 1,2, Tomasz Piotrowski 1 and Edward Gorzelańczyk 3 1 Department.
Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved. Decision Support Systems Chapter 10.
Computational Intelligence: Methods and Applications Lecture 37 Summary & review Włodzisław Duch Dept. of Informatics, UMK Google: W Duch.
Annotating Words using WordNet Semantic Glosses Julian Szymański Department of Computer Systems Architecture, Faculty of Electronics, Telecommunications.
Computational Intelligence: Methods and Applications Lecture 30 Neurofuzzy system FSM and covering algorithms. Włodzisław Duch Dept. of Informatics, UMK.
Some working definitions…. ‘Data Mining’ and ‘Knowledge Discovery in Databases’ (KDD) are used interchangeably Data mining = –the discovery of interesting,
ICDM 2003 Review Data Analysis - with comparison between 02 and 03 - Xindong Wu and Alex Tuzhilin Analyzed by Shusaku Tsumoto.
Computational Intelligence: Methods and Applications Lecture 20 SSV & other trees Włodzisław Duch Dept. of Informatics, UMK Google: W Duch.
Data Mining In contrast to the traditional (reactive) DSS tools, the data mining premise is proactive. Data mining tools automatically search the data.
Towards CI Foundations Włodzisław Duch Department of Informatics, Nicolaus Copernicus University, Toruń, Poland Google: W. Duch WCCI’08 Panel Discussion.
Data Mining and Decision Trees 1.Data Mining and Biological Information 2.Data Mining and Machine Learning Techniques 3.Decision trees and C5 4.Applications.
BOĞAZİÇİ UNIVERSITY DEPARTMENT OF MANAGEMENT INFORMATION SYSTEMS MATLAB AS A DATA MINING ENVIRONMENT.
WEEK INTRODUCTION IT440 ARTIFICIAL INTELLIGENCE.
Fundamentals of Information Systems, Third Edition1 The Knowledge Base Stores all relevant information, data, rules, cases, and relationships used by the.
On the computer-aided problem-solving and research Szeged Winter Training 2015 The project is co-financed by the European Union.
Cognitive Science Overview Introduction, Syllabus
Artificial Intelligence, simulation and modelling.
WHAT IS DATA MINING?  The process of automatically extracting useful information from large amounts of data.  Uses traditional data analysis techniques.
Artificial Intelligence
Data Mining is the process of analyzing data and summarizing it into useful information Data Mining is usually used for extremely large sets of data It.
Brief Intro to Machine Learning CS539
The 14th International Conference on Neural Information Processing (ICONIP2007) ICONIP 2007 참관기 홍진혁.
Classification of models
Support Feature Machine for DNA microarray data
Computer Science Courses
SIMULATION SIMULAND PURPOSE TECHNIQUE CREDIBILITY PROGRAMMATICS
Spring 2003 Dr. Susan Bridges
RESEARCH APPROACH.
We teach ATM Networks to Think
Artificial Intelligence and Lisp Lecture 13 Additional Topics in Artificial Intelligence LiU Course TDDC65 Autumn Semester,
Department of Informatics (KIS) Nicolaus Copernicus University
Future Technologies FTC 2016 Future Technologies Conference December 2016 San Francisco, United States.
What is Pattern Recognition?
Basic Intro Tutorial on Machine Learning and Data Mining
Automatic Discovery of Shared Interest Minimum Spanning Trees Displaying Semantic Similarity Włodzisław Duch & Co Department of Informatics, Nicolaus.
Announcements Research Topic – finalize by 9/22 – topics so far
Computational Intelligence: Methods and Applications
Fuzzy rule-based system derived from similarity to prototypes
کتابهای تازه خریداری شده دروس عمومی 1397
Heterogeneous adaptive systems
Welcome! Knowledge Discovery and Data Mining
Computer Science Courses in the Major
The Curriculum of the Department of Informatics TEI-A
Presentation transcript:

Department of Informatics, Nicolaus Copernicus University, Toruń Department of Informatics, Nicolaus Copernicus University, Toruń. Head: Włodzisław Duch (Google: Duch); also at School of Computer Engineering, Nanyang Technological University, Singapore. Main fields: neural networks, similarity-based systems, decision trees, visualization, natural language processing, data and Web mining, extraction of logical rules, data understanding, bioinformatics Papers archive: http://www.phys.uni.torun.pl/kmk/papers.html New computational intelligence models: Feature Space Mapping (FSM) neurofuzzy system based on separable basis function network, & IncNet ontogenic network (growing, shrinking, merging), with novel transfer functions. Separability Split Value (SSV) decision trees for classification, selection of information, discretization of features, and extraction of logical rules. Framework for Similarity Based systems, SB Learner (SBL) software. These and other algorithms are in the GhostMiner data mining package, marketed by Fujitsu Systems http://www.fqspl.com.pl/ghostminer/

Current projects of the Department of Informatics, Nicolaus Copernicus University, Toruń. Development of the GhostMiner functionality and software. Development of heterogeneous CI systems based on mixed neural functions, similarity measures and decision tree tests. Understanding of neural network mappings via visualization, improving neural training algorithms. CI applications in medical informatics and bioinformatics (with Children’s Hospital Research Foundation, Cincinnati, Ohio, USA). Natural language processing: web applications, medical applications, word games, in particular 20 question game. Development of humanized interfaces, talking heads with natural communication abilities (large project with NTU, Singapore). Artificial Brain Architecture and Cognitive Control Understanding System (ABACCUS, Integrated European FP6 project, submitted). Cognitive toys interacting with children (with Cincinnati). Understanding brain functions, connecting psychology with neuroscience, specifying requirements for conscious systems.