'Domain knowledge' diaporamas de présentation

Artificial Intelligence SS 2017

Artificial Intelligence SS 2017. CommonKADS Anna Fensel 03.04.2017. Where we are. Agenda. Motivation Technical solution, illustrations and extensions Overview of CommonKADS Knowledge model components Template knowledge models Knowledge model construction

1.64k views • 144 slides

Artificial Intelligence WS 2015/16

Artificial Intelligence WS 2015/16. CommonKADS Anna Fensel. Where are we?. Agenda. Motivation Technical solution, illustrations and extensions Overview of CommonKADS Knowledge model components Template knowledge models Knowledge model construction Knowledge elicitation techniques

1.56k views • 144 slides

Effect of Support Distribution

Effect of Support Distribution. Many real data sets have skewed support distribution. Support distribution of a retail data set. Effect of Support Distribution. How to set the appropriate minsup threshold?

895 views • 75 slides

Robust real-time face detection

865 views • 60 slides

ONTACWG: Coordinating Knowledge Classifications

ONTACWG: Coordinating Knowledge Classifications. Patrick Cassidy MITRE Corporation* Presented at the ONTACWG Organization Meeting October 5, 2005 McLean, Virginia

821 views • 58 slides

Todd Little, Niel Nickolaisen and Pollyanna Pixton

A Framework for Agile Leadership Agile 2007. L e a d i n g C h a n g e T h r o u g h C o l l a b o r a t i o n. Todd Little, Niel Nickolaisen and Pollyanna Pixton. Declaration of Interdependence. Frameworks Strategy: Niel Nickolaisen Collaboration: Pollyanna Pixton

660 views • 47 slides

ITEC 4010: Systems Analysis and Design II.

ITEC 4010: Systems Analysis and Design II. Professor Peter Khaiter. Lecture 7 Requirements Determination. Principles of Requirements Determination Requirements Elicitation Requirements Negotiation and Validation Requirements Management Problem Statements for Case Studies

861 views • 39 slides

Data-driven methods in Environmental Sciences Exploration of Artificial Intelligence Techniques

Data-driven methods in Environmental Sciences Exploration of Artificial Intelligence Techniques. Valliappa.Lakshmanan@noaa.gov. Data Driven Methods. What is Artificial Intelligence? Common AI techniques Choosing between AI techniques Pre and post processing. What is AI?.

667 views • 34 slides

Innovation and Technology in Assessment: Comments

Innovation and Technology in Assessment: Comments. Eva L. Baker Director National Center for Research on Evaluation, Standards, & Student Testing UCLA Public and Expert Input Meeting, Race to the Top, U.S. Department of Education Boston, MA November 12-13, 2009.

475 views • 33 slides

Efficient Record Linkage in Large Data Sets

Efficient Record Linkage in Large Data Sets. Liang Jin, Chen Li , Sharad Mehrotra University of California, Irvine. DASFAA, Kyoto, Japan, March 2003. Motivation . Correlate data from different data sources (e.g., data integration) Data is often dirty

630 views • 32 slides

Unsupervised Ontology Induction From Text

582 views • 31 slides

Knowledge-based Information Retrieval: A Work in Progress

Knowledge-based Information Retrieval: A Work in Progress. Knowledge-based Systems Research Group, University of Texas at Austin. Shortcomings of Current IR Systems: Hard Questions. Query: Where does Al Qaeda operate? ? rephrase as a Jeopardy-style question:

453 views • 31 slides

Troubleshooting Chronic Conditions in Large IP Networks

Troubleshooting Chronic Conditions in Large IP Networks. Ajay Mahimkar , Jennifer Yates, Yin Zhang, Aman Shaikh, Jia Wang, Zihui Ge, Cheng Tien Ee UT-Austin and AT&T Labs-Research mahimkar@cs.utexas.edu ACM CoNEXT 2008. Network Reliability.

392 views • 25 slides

JLAB Data Acquisition Run Control System

JLAB Data Acquisition Run Control System. Jefferson Lab Vardan Gyurjyan. Run-control history. Eiffel C++ Java. Run-control design requirements. Extendable. Network distributed. Platform independent. Software centric. Flexible. Dynamic hierarchical.

346 views • 16 slides

Subject-based Network for Ayurveda

Subject-based Network for Ayurveda. Faculty of Ayurveda Institute of Medical sciences Banaras Hindu University Varanasi-221005 Email: sbnayurvedabhu@gmail.com. Objectives.

338 views • 14 slides

On the Testing Maturity of Software Producing Organizations

On the Testing Maturity of Software Producing Organizations. Mats Grindal Jeff Offutt Jonas Mellin. The study. Informal observations over 10+ years of consultancy indicate low test maturity Goal: assess and document aspects of test maturity Method: Interviews with test managers

248 views • 14 slides

SOMEDAY YOU WILL REAP WHAT YOU SOW India: The New Global Business Opportunity

SOMEDAY YOU WILL REAP WHAT YOU SOW India: The New Global Business Opportunity. Arun Maira The Boston Consulting Group. San Francisco. Intense competition between firms in developed countries in their own developed country markets Competition between firms for customers in developing countries

442 views • 13 slides

Detection and Analysis

Detection and Analysis. Perspectives of Both Data Monitors and Algorithm Developers. Data Monitors. Turbulence Turnover Training Varied skill sets Limited understanding of algorithms Overworked and few Feedback to providers critical. Developers.

223 views • 12 slides

Dendral: A Case Study

413 views • 11 slides

The good, the bad, and the ugly

The good, the bad, and the ugly. Ugly: Most IS implement ad hoc solutions to T+C Good: Managing T+C is not the bottleneck in developing MIIS Many turn-taking / control issues can be solved by a priori analysis or explicit run-time negotiation Bad: Domain knowledge is still king.

348 views • 4 slides