CSIT600G: Knowledge Management

CSIT600G: Knowledge Management (3 credits)

Prof. Dekai WU
Human Language Technology Center
Department of Computer Science
Hong Kong University of Science & Technology
HKUST, Clear Water Bay, Hong Kong
dekai@cs.ust.hk
http://www.cs.ust.hk/~dekai
© 2007.06.04 Dekai Wu

Introduction

Welcome to CSIT600G for Summer 2007! We meet Tuesdays and Thursdays in Room 6580 (lifts 27-28) on the following dates:

Track 8 (FT class admitted Fall 2006) meets 15:00--17:50, and Track 9 (PT class admitted Fall 2006) meets 19:30--22:20.

Course home page: http://www.cs.ust.hk/~dekai/600G/
Forum: http://comp151.cse.ust.hk/~dekai/content/?q=forum/1

Course description

Thorough coverage of the latest theory and practice of Knowledge Management (KM), with an integrated interdisciplinary presentation that makes sense of the confusingly wide variety of computer science and business KM perspectives arising simultaneously from artificial intelligence, information systems, and organizational behavior. Solidly covers the "hard" technical components of computer tools and technology for managing knowledge, without losing sight of the "soft" management needs and challenges in leveraging knowledge effectively within an organization. Critically evaluates the nature, computer representation, access, and utilization of knowledge versus information within a human context. Essential preparation for managerial, technical, and systems workers alike in today's modern knowledge-based economy.

Course objective

The goal of this course is to give you a solid foundation covering the major problems, challenges, concepts, and techniques dealing with the organization and management of knowledge with the help of computers. Upon satisfactory completion of this course, you can expect to:

You will understand how to exploit systems to offer support to modern knowledge workers, in particular with respect to the rapidly increasing overload of knowledge and information that is available and necessary to stay competitive for many tasks. This includes support for traditional Knowledge Management tasks, such as the grouping of related documents into categories or hierarchies, the generation of dictionaries and ontologies, or the construction of knowledge networks through references and citations. We also study how methods and techniques that rely on computers can be used to augment the human-centered tasks. Examples for such approaches are automatic content- and usage-based categorization of documents, collaborative filtering, or the extraction of relevant key phrases from documents, case-based reasoning, data and text mining, and information extraction and summarization.

In contrast to knowledge-based systems, where computers manipulate and generate knowledge as standalone agents, the goal of Knowledge Management is to use computers as practical tools for activities mainly performed and directed by humans within real modern-day knowledge-based organizations.

"If we only knew what we know, we'd all be a lot smarter." - Lew Platt, CEO, Hewlett Packard

Textbook

Reference books/materials

Grading scheme

Project

In your final group project, you will take the case your group has constructed up to Chapter 5, and extend it so that your recommendation also includes detailed specifications incorporating one or more of the most appropriate technologies after Chapter 6. You should include sufficient detail that it is clear what implementation would require. This includes, but is not limited to, your methodology for knowledge engineering, capture, and acquisition; the types of engines needed; the types of features, attributes, rules, chaining, cases, indexes, metrics, mining; etc.

Note that the final project is due on or before Dec 14. Your group should turn in a written report, much as if you were a consulting group delivering the final report to the CEO. (In general, PowerPoint presentations are not adequate, unless they are truly exceptional, and read just as clearly and detailed as a normal report would.)

Syllabus

Date Topic Notes Reading
 
Principles, Case Studies
2007.06.05 Overview of Knowledge Management Ch1
2007.06.07 The Nature of Knowledge Ch2
2007.06.12 Knowledge Management Solutions Ch3
2007.06.14 Organizational Impacts of Knowledge Management Ch4
2007.06.19 Factors Influencing Knowledge Management Ch5
2007.06.19 Knowledge Management Assessment of an Organization Ch6
Technologies
2007.07.17 Technologies to Manage Knowledge: Artificial Intelligence, Digital Libraries, Repositories, etc. Ch7
2007.07.17 Preserving and Applying Human Expertise: Knowledge-Based Systems Ch8
2007.07.19 Using Past History Explicitly as Knowledge: Case-Based Systems Ch9
2007.07.24 Knowledge Elicitation: Converting Tacit Knowledge to Explicit Ch10
2007.07.26 Discovering New Knowledge: Data Mining Ch12
2007.07.31 Text KM & Text Mining
Systems
2007.08.02 Knowledge Discovery: Systems that Create Knowledge Ch13
2007.08.02 Knowledge Capture Systems: Systems that Preserve and Formalize Knowledge; Concept Maps, Process Modeling, RSS, Wikis, Delphi Method, etc. Ch14
2007.08.07 Knowledge Sharing Systems: Systems that Organize and Distribute Knowledge; Ontology Development Systems, Categorization and Classification Tools, XML-Based Tools, etc. Ch15
2007.08.07 Knowledge Application Systems: Systems that Utilize Knowledge Ch16
Looking Forward
2007.08.09 What to Expect: The Future of Knowledge Management Epilogue
2007.08.09 Group Project due