Knowledge Management

"Knowledge management is a relatively new and developing area which has introduced a methodology for the planned capture and re-use of organisational knowledge. ... Our analyses have concentrated on how [AI] techniques can enable a more efficient access, sharing and usage of accumulated knowledge as a means of enabling different functions within the organisation to perform their tasks more effectively." - Colquhoun-John Ferguson & Scott Goldie

The Road Ahead for Knowledge Management: An AI Perspective. By Reid G. Smith and Adam Farquhar. AI Magazine 21(4): Winter 2000, 17-40. "Enabling organizations to capture, share, and apply the collective experience and know-how of their people is seen as fundamental to competing in the knowledge economy. As a result, there has been a wave of enthusiasm and activity centered on knowledge management. To make progress in this area, issues of technology, process, people, and content must be addressed. In this article, we develop a road map for knowledge management. It begins with an assessment of the current state of the practice, using examples drawn from our experience at Schlumberger. It then sketches the possible evolution of technology and practice over a 10-year period. Along the way, we highlight ways in which AI technology, present and future, can be applied in knowledge management systems."

The Road Ahead and other KM articles by Reid G. Smith, as well as aKM Glossary, are available from the resource collection provided by R.G. Smith & Associates, a knowledge management company.

AI Knows It’s Out There. Red Herring (August 22, 2005 print issue). "Another branch of search-related AI is content management, which involves organizing data that does not come in structured formats, explains Lubor Ptacek, director of marketing for the Documentum line of content management software at EMC in Hopkinton, Massachusetts. The AI involves understanding various document formats to give the documents a common architecture in a single repository."

• Have a look at Documentum's Content Intelligence Services and be sure to also check out the other companies & products mentioned in the article.

Knowledge Management at the Artificial Intelligence Applications Institute, School of Informatics, The University of Edinburgh. "AIAI is concerned with how specific aspects of AI, namely modelling, ontologies and planning techniques can support knowledge management. These techniques allow an integrated support framework to be developed for knowledge management based on adaptive workflow techniques."

The SEKT Project [Semantically-Enabled Knowledge Technologies]: "The vision of SEKT is to develop and exploit the knowledge technologies which underlie Next Generation Knowledge Management. We envision knowledge workplaces where the boundaries between document management, content management, and knowledge management are broken down, and where knowledge management is an effortless part of day to day activities. Appropriate knowledge is automatically delivered to the right people at the right time at the right granularity via a range of user devices. Knowledge workers will be empowered to focus on their core roles and creativity; this is key to European competitiveness."

• SEKT Demo: "The SEKT concept demonstrator has been created to show the business potential of SEKT technology. The scenario is set in the financial services sector, but the ideas can be easily extrapolated to a range of sectors and application domains."
  • More demos of the software tools developed in the SEKT project.
• Background Technologies: Ontology & Metadata Technology, Human Language Technology, and Knowledge Discovery.
• Project partners, co-funded by the EU 6th Framework programme.

Knowledge Management Laboratory at DFKI, the German Research Center for Artificial Intelligence. "Knowledge represents the intellectual principal of any corporation. Its organization, structure and communication are essential for economic success, customer relations, and strategic planning. Sustainable corporate governance nowadays requires active and extensive knowledge management based on powerful and efficient organizational memories. The main task is to enable lean, decentralized and continuously learning organizations to act both flexibly and coherently at the same time. Directed by Prof. Dr. Andreas Dengel, the Knowledge Management Laboratory develops technologies that allow to prepare, update, allocate, store and communicate information, data and knowledge precisely and systematically. Our objective is to develop automated personal knowledge assistants that support the configuration of workflows as well as pro-actively provide relevant information in any setting."

Applied Artificial Intelligence and the Management of Knowledge. By Colquhoun-John Ferguson & Scott Goldie, Department of Management & Marketing University of Paisley. Bristol Business School Teaching and Research Review, Issue 3, Summer 2000. "Our current research addresses the question of how artificial intelligence (AI) tools may facilitate the organising, disseminating, storing and interpreting of knowledge. Two (AI) techniques have formed the focus for our research with the aim of combining these techniques into a hybrid system to manage the interpretation of corporate data and information for use by product designers: case -based reasoning and data mining."

Refiningenterprise search - Enterprise search is reaping relevant resultsthanks to new platforms and technologies. By Richard Gincel. InfoWorld(October 15, 2004). "[M]ostenterprise users still stumble as they try to extract data from multiplerepositories, each with its own search engine. Enterprises seem awashin a rising tide of structured and unstructured data. And even thoughusers are often forced to tag documents manually across various contentmanagement systems in hopes that those documents will be easier toretrieve, searches still yield a surfeit of irrelevant, time-wastingresults. ESPs (enterprise search platforms) are on a mission to changeall that. These new, comprehensive bundles of search and integrationtechnologies unlock information tucked away in data stores acrossthe enterprise. The goal of ESPs is deceptively simple: to take fairlysimple queries and return the most relevant results possible, allin one place. But under the hood, ESPs aggregate a host of emergingtechnologies such as autocategorization, entity extraction, and NLP(natural language processing). With an ESP as a foundation, businessescan build customized search applications while automating the processof preparing documents for archiving and indexing."

Searching for KM. By Robert J. Boeri. EContent Magazine (January 2003). "Knowledge Management is a term that goes in and out of favor. Whatever name you give it though, consistently capturing and reusing intellectual assets is a critical endeavor within an organization that values information-sharing. ... In all search systems, results improve when queries provide more restrictions. ... The key point is how each system delivers the most useful search results without omitting important ones, leveraging the strengths of its system design. ... Autonomy's core strength is Bayesian statistical techniques. Its search system can learn what users consider relevant, simplifying and improving search results over time, but requires well-selected samples to learn from. Convera's design is based on fuzzy logic and neural network technology. When natural language is important or searching scanned documents with their inevitable optical character recognition spelling errors, Convera may have the edge. Each vendor has its own spin on the advantage of its enterprise solution."

Humans vs. Computers, Again. But There's Help for Our Side. By James Fallows. The New York Times (April 18, 2004; subscription req'd.). "We've seen this pattern before in the computer world: many companies scrambling at the same time to solve the same problem. Sometimes the concentration of effort mainly ends up underscoring how hard it can be to solve a given problem, like controlling spam.... But often such races result in true breakthroughs that make computers much more useful and creates countless opportunities for follow-on innovations and products. ... A current race for a solution goes by the deceptively blah name of 'knowledge management,' or K.M. It is an effort to bring Google-like clarity to the swamp of data on each person's machine or network, and it is based on the underappreciated tension between a computer's capacity and a person's. Modern computers 'scale' well, as the technologists say - that is, the amount of information they can receive, display and store goes up almost without limit. Human beings don't scale. ... The current creative struggle is important because, when it yields a victor, it will leave everyone less frustrated about using a computer. ... On the conceptual level, it raises basic questions about what knowledge is. ... The underlying intellectual question about knowledge management is whether people actually think of knowledge as a big heap of laundry just out of the dryer, or as neatly folded pajamas, shirts and so on, all placed in the proper drawers."

Sniper probe to get help from Tucson. By L. Anne Newell. Arizona Daily Star (October 23, 2002). "A program developed by Tucson police and the University of Arizona will be used to try to capture the Washington, D.C.,-area sniper... COPLINK works by combining databases, limiting the number of individual searches officers have to perform. They can enter partial vehicle and suspect descriptions and the program will locate everyone who fits the description. ... The program - developed at the UA Artificial Intelligence Lab and funded through grants from the National Institute of Justice and the National Science Foundation - is also being used in Texas, Michigan, Massachusetts, Iowa and Washington state. ... [Sgt. Randy Force] said it will be especially helpful to his department for the same reason it should help authorities in the Washington, D.C., area: It helps alleviate many burdens of multi-jurisdictional cases. There are about 20 law enforcement agencies in the greater Phoenix area, he said."

• Related resources can be found on our Law Enforcement page, the News Archive (see for example: October 2002), and in these articles:

Collective Knowledge Bases. From the University of Washington Artificial Intelligence Research Group. "The production and use of knowledge is a collective enterprise, and communication between its participants is the bottleneck. Some of the costs of this bottleneck are duplicated work, misdirected work, slower progress, and suboptimal decisions for lack of knowledge that is actually available. ... In particular, we are developing methods to improve the composability of knowledge by semi-automatically learning to translate between the vocabularies of different sources. This can potentially lead to an exponential increase in the number of questions answerable by a collective knowledge base. We are also developing methods to automatically learn the quality of knowledge sources and elements, to properly take advantage of sources of widely variable quality, to automatically resolve inconsistencies between sources, and to automatically give feedback, credit and guidance to contributors, such that a collective knowledge base can grow and improve harmonically without centralized control."

The Role of Artificial Intelligence in Knowledge Management. Editorial Note by Eric Tsui, Brian Garner and Steffen Staab. Knowledge-Based Systems, 13(5): 235-239. Elsevier, 2000. Available from Steffen Staab's publications page (Journals: 2000).

Knowledge Management Overview from PortBlue. "The theory behind these products is that the freshest and most dynamic source of knowledge within an organization is the stream of documents, e-mails, and data produced as a normal by-product of conducting business. By filtering, sorting, and re-combining this information, electronic tools can provide access to an organization's intellectual capital with little or no incremental effort by the experts producing this material. ... [M]ore formal approaches include:... Building expert systems to capture and apply an expert's rule set." Also see:

• PortBlue answers the question: What are Expert Systems?
• An article about PortBlue: New Tools Help Hospitals Handle Terror Attacks And Other Disasters. By Marianne Kolbasuk McGee. InformationWeek (April 14, 2005)

Haley Systems, Inc. "f the speed of change is putting a strain on your IT resources and bottom line, a Business Rules Management System (BRMS) can give you the agility you need to outpace the competition. By externalizing frequently changing business logic from your applications, a BRMS empowers business users to change the 'business rules' - such as policies and procedures - without the time and expense of IT programming." Products include:

• HaleyAuthority: "business rules management application, empowers business and IT users to capture, organize, test, and deploy business logic in your own natural business language so you can manage business rules - those associated with automated decision-making in IT applications and business processes -- in real time."
• HaleyRules: "business rules engine, automates decision-making in applications and business processes so enterprises can manage business rules quickly, while significantly reducing programming needs, time-to-market, and application lifecycle costs."

Algorithms & data management glossary. From the Cambridge Healthtech Institute. AI, data mining, knowledge management and more!

Knowledge Management & Discovery at Stottler Henke Associates, Inc.: "Our knowledge management systems capture the knowledge of in-house experts as rules, models, and case bases of previously encountered situations and solutions. These knowledge repositories enable advisory systems that help companies assess situations, diagnose and repair problems, and design products and processes more quickly and consistently. Our knowledge discovery systems extract valuable knowledge from large databases and help people conduct comprehensive online research."

Enterprise Knowledge Management, by Daniel E. O'Leary Computer (March 1998, pages 54 - 61). Also available from the ResearchIndex. "As employees turn over in today's overheated job market, organizations are likely to lose access to large quantities of critical knowledge. Can we create a system that will capture company-wide knowledge and make it widely available to all its members?"

Indian software product industry comes of age. By R.P. Srikanth. Express Computer India (May 5, 2003). "As a large conglomerate with heavy spending, GE was in need of a solution that could reduce purchasing cycle time, improve process efficiency and accountability and reduce procurement costs. And a product based on Artificial Intelligence algorithms fit GE’s needs to perfection. Autoclass, which is available in both Live connect and Batch connect modes, is a perfect solution for big corporates like GE who are looking to find answers in their chaotic reams of data."

Knowledge Management Projects at IBM's Tokyo Research Laboratory. "The discovery of significant patterns by computer analysis of very large amounts of data can reveal new knowledge. There will be various new business opportunities if the newly-discovered knowledge can be used effectively. TRL's technologies and algorithms for information analysis have been applied in many industries, such as finance, logistics, manufacturing, and medical care."

"SAGE [Searchable Answer Generating Environment] is a Knowledge Management (KM) system that aims to create the first repository of experts in the State of Florida. Currently, each of the State Universities in Florida maintain information concerning funded research, but these databases are disparate and disjoint. The SAGE application creates one single web-enabled repository which can be searched in a number of ways including RESEARCH TOPIC, INVESTIGATOR NAME, FUNDING AGENCY, or UNIVERSITY."

• The Role of Artificial Intelligence Technologies in the Development of Knowledge Management Systems. This announcement for a NASA seminar offers a nice overview of SAGE and The Expert Seeker KMS.
• And here's a paper by Professor Irma Becerra-Fernandez, Ph.D., the speaker at the previously mentioned NASA seminar: The Role of Artificial Intelligence Technologies in the Implementation of People-Finder Knowledge Management Systems.

Knowledge Management Laboratory at Florida International University, College of Business Administration, Department of Decision Science and Information Systems. Tutorial: AI Techniques for Knowledge Management. By S. Decker & S. Staab. ECAI-2000 Tutorial Berlin, August, 21-22, 2000.

Engineer foresaw computer, built precursor. Vannevar Bush made differential analyzer. By Paula Schleis. Akron Beacon Journal / Ohio.com (April 27,2004). "A machine on a desk can access the collective knowledge of the human race. Touch a button, and millions of repositories are searched with lightning speed. ... This is how Vannevar Bush described the modern computer. In 1945. The Atlantic Monthly published his musings as World War II was coming to an end. The scientist urged his peers to redirect their wartime energy toward making the world's knowledge more accessible. The groundbreaking piece of prose has been credited with not only influencing the design of the personal computer, but inspiring the hypertext language that made the World Wide Web possible. ... He led a group of colleagues in developing the differential analyzer, the most advanced calculator of its time. ... He predicted artificial intelligence -- computers that would act when spoken to and type text that is dictated into a microphone. ... Bush's essay also gave the world a reason to pursue the dream: mankind's future depended on it. Knowledge that could improve and save lives was being lost in a mountain of paper that was fragile, far flung and unorganized."

More Readings

Exploring Synergies of Knowledge Management and Case-Based Reasoning: Papers from the 1999 AAAI Workshop, ed. David Aha, Irma Becerra-Fernandez, Frank Maurer, and Hector Munoz-Avila. Technical Report WS-99-10. American Association for Artificial Intelligence, Menlo Park, California. As stated in the editors' preface: "Knowledge management is an exciting emerging discipline within AI. One attraction is that KM provides close ties with industry that allows for researchers to focus their work on important real-world problems. KM also challenges AI with interesting issues concerning how to define, acquire; disseminate, and maintain knowledge in a distributed organizational setting. Several CBR researchers and practitioners firmly believe that case-based reasoning has a role to play in knowledge management. This workshop is devoted to enhancing the communication between KM and CBR researchers and practitioners, and to identify their potential synergies."

Knowledge Management Systems - A Text Mining Perspective. By Hsinchun Chen, Ph.D, McClelland Endowed Professor of Management Information Systems, Department of Management Information Systems, Eller College of Business and Public Administration, The University of Arizona. (2001). He is the Director of the Artificial Intelligence Lab.

Artificial Intelligence in Knowledge Management: Papers from the 1997 Spring Symposium, ed. Brian R. Gaines and Ramasamy Uthurusamy. Technical Report SS-97-01. American Association for Artificial Intelligence, Menlo Park, California. "Knowledge management (KM) is a topic of growing interest to large organizations. It comprises activities focused on the organization acquiring knowledge from many sources, including its own experience and from that of others, and on the effective application of that knowledge to fulfill the mission of the organization.The knowledge management community has been eclectic in drawing from many sources for its methodologies and tools. Typical approaches to the management of knowledge are based on concept maps, hypermedia, and object-oriented databases. Techniques developed in artificial intelligence for knowledge acquisition, representation and discovery are seen as relevant to KM. However, there is as yet no unified underlying theory for KM, and the scale of the problem in large organizations is such that most existing AI tools cannot be applied in their current implementations.The objective of this symposium was to bring together KM practitioners and applied AI specialists from KA, KR and KDD, and attempt to formulate the potential role of various AI sub-disciplines in knowledge management."