Future of Knowledge Management Systems Logan Buchanan December 8, 2005
References <ul><li>Ackerman, M. S (1994). Augmenting Organizational Memory: A Field Study of Answer Garden. </li></ul><ul>...
Answer Garden <ul><li>Field study  </li></ul><ul><ul><li>Group of users and group of experts. </li></ul></ul><ul><li>Users...
Expertise Recommender <ul><li>Architecture open and flexible enough to address different organizational environments. </li...
YouServ <ul><li>Pool existing desktop computing resources for high quality web hosting and file sharing. </li></ul><ul><ul...
Oval <ul><li>Create applications by combining and modifying objects, views, agents, and links (or Oval). </li></ul><ul><li...
Oval cont. <ul><li>gIBIS - a tool for helping a group explore and capture the qualitative factors that go into making deci...
Autonomous Interface Agents <ul><li>Interface agents = software that actively assists a user in operating an interactive i...
SOAP <ul><li>Social agents interact with one another on behalf of their clients </li></ul><ul><ul><li>Examples: agents for...
Social Information Filtering <ul><li>Social information filtering automates the process of “word-of-mouth” recommendations...
Agents <ul><li>Building Agents </li></ul><ul><ul><li>Two main problems </li></ul></ul><ul><ul><ul><li>Competence: how does...
The Semantic Web <ul><li>An extension of the current Web, in which information is given well-defined meaning. </li></ul><u...
KM on the Semantic Web <ul><li>Semantic Web can serve as a platform for developing knowledge management systems. </li></ul...
An Agent Based Approach to Knowledge Management <ul><li>MARS, a multiagent referral system for knowledge management </li><...
Upcoming SlideShare
Loading in …5
×

Future Of Knowledge Management Systems

952 views
894 views

Published on

Published in: Education, Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
952
On SlideShare
0
From Embeds
0
Number of Embeds
8
Actions
Shares
0
Downloads
98
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide
  • Future Of Knowledge Management Systems

    1. 1. Future of Knowledge Management Systems Logan Buchanan December 8, 2005
    2. 2. References <ul><li>Ackerman, M. S (1994). Augmenting Organizational Memory: A Field Study of Answer Garden. </li></ul><ul><li>Ackerman, M. S. & McDonald, D.W. (1996) Answer Garden 2: Merging Organizational Memory with Collaborative Help. </li></ul><ul><li>McDonald, David & Ackerman, Mark. (2000)Expertise Recommender: A Flexible Recommendation System and Architecture. Proceedings of CSCW'00. ACM Press. </li></ul><ul><li>Bayardo, R., Agrawal, R., Gruhl, D., Somani, A. (2002) YouServ: A Web Hosting and Content Sharing Tool for the Masses. WWW2002, May 7-11, 2002, Honolulu, Hawaii, USA </li></ul><ul><li>Malone, Lai, & Fry. Experiments with Oval: A Radically Tailorable Tool for Cooperative Work </li></ul><ul><li>Lieberman, H. (1997). Autonomous Interface Agents. ACM Conference on Human-Computer Interface [CHI-97], Atlanta, ACM Press. </li></ul><ul><li>Voss, A. and Kreiflets, T. (1997) SOAP: Social Agents Providing People With Useful Information. Proceedings of GROUP'97, ACM Press, pp. 291-298. </li></ul><ul><li>Shardanand, U. & Maes, P. (1995) Social information filtering: algorithms for automating &quot;word of mouth&quot;. Conference proceedings on Human factors in computing systems. ACM Press. </li></ul><ul><li>Maes, P. (1994) Agents That Reduce Work and Information Overload. Communications of the ACM, 37(7), 31-40. </li></ul><ul><li>Berners-Lee, T., Hendler, J. and Lassila, O. (2001) The Semantic Web. Scientific American, May 2001. </li></ul><ul><li>Stojanovic, Nenad & Handschuh, Siegfried. (2002) A Framework for Knowledge Management on the Semantic Web. Proceedings of the World Wide Web conference 2002. Honolulu. </li></ul><ul><li>Yu, Bin & Singh, M. (2002) An Agent-Based Approach to Knowledge Management. CIKM'02. McLean, VA. ACM Press. </li></ul>
    3. 3. Answer Garden <ul><li>Field study </li></ul><ul><ul><li>Group of users and group of experts. </li></ul></ul><ul><li>Users </li></ul><ul><ul><li>Need for speed </li></ul></ul><ul><ul><li>Social network and information retrieval system worked well together. </li></ul></ul><ul><ul><li>Status implications. </li></ul></ul><ul><li>Experts </li></ul><ul><ul><li>Some refused to answer based on their workload. </li></ul></ul><ul><ul><li>Incentives questionable. </li></ul></ul><ul><li>Answer Garden 2 </li></ul><ul><ul><li>No separate groups. </li></ul></ul><ul><ul><li>Contextualize answers. </li></ul></ul><ul><ul><li>Escalation. </li></ul></ul><ul><ul><li>Being anonymous is optional. </li></ul></ul>
    4. 4. Expertise Recommender <ul><li>Architecture open and flexible enough to address different organizational environments. </li></ul><ul><li>Organizationally specific implementations. </li></ul><ul><li>User profiles created from organizationally relevant data sources such as work products. </li></ul><ul><li>Allows for user choice. </li></ul><ul><li>Recommendations can be revisited and escalated if necessary. </li></ul>
    5. 5. YouServ <ul><li>Pool existing desktop computing resources for high quality web hosting and file sharing. </li></ul><ul><ul><li>Assigned a domain name. </li></ul></ul><ul><ul><li>Pool resources of a group - content can be accessed when your computer is off. </li></ul></ul><ul><ul><li>Can publish even if behind a firewall. </li></ul></ul><ul><ul><li>Low cost. </li></ul></ul><ul><li>Alternative to e-mailing attachments. </li></ul><ul><li>Photo sharing is predicted most common use. </li></ul>
    6. 6. Oval <ul><li>Create applications by combining and modifying objects, views, agents, and links (or Oval). </li></ul><ul><li>Tailorable = end users can modify a working system (such as a spreadsheet), changes are made in the context of a working application </li></ul><ul><li>Radical = large changes can be made </li></ul><ul><li>User interface is simple and provides a “large amount of functionality for creating and modifying a wide range of applications” </li></ul>
    7. 7. Oval cont. <ul><li>gIBIS - a tool for helping a group explore and capture the qualitative factors that go into making decisions </li></ul><ul><li>Sibyl - goals for decisions and previous decisions </li></ul><ul><li>Coordinator - an e-mail based system that helps people structure conversations and track tasks. </li></ul><ul><li>Lotus Notes </li></ul><ul><li>Intelligent Lens - automatically filters and sorts incoming e-mail </li></ul><ul><li>Answer Garden </li></ul><ul><li>And… a database of people, an organization chart, a project management system, a system for tracking software bug reports, a system for supporting marketing decision making, a system for supporting quality management processes in manufacturing, and a workflow system for purchase-order approval. </li></ul>
    8. 8. Autonomous Interface Agents <ul><li>Interface agents = software that actively assists a user in operating an interactive interface </li></ul><ul><li>Autonomous agents = software that takes action without user intervention and operates concurrently </li></ul><ul><li>Letizia </li></ul><ul><ul><li>An autonomous interface agent for Web browsing. </li></ul></ul><ul><ul><li>Records URLs chosen by the user and reads the pages to compile a profile of the user’s interests. </li></ul></ul><ul><li>Work best in situations where their decisions are not critical, such as web browsing. </li></ul>
    9. 9. SOAP <ul><li>Social agents interact with one another on behalf of their clients </li></ul><ul><ul><li>Examples: agents for electronic markets, workflow agents, information brokers </li></ul></ul><ul><li>New users register in order to obtain a personal user agent. A user agent links the user and the other agents. </li></ul><ul><li>For each query, a task agent is created. </li></ul><ul><li>There are also group agents, recommender agents, and search agents, directory agents, etc. </li></ul>
    10. 10. Social Information Filtering <ul><li>Social information filtering automates the process of “word-of-mouth” recommendations. </li></ul><ul><ul><li>General trends and patterns within the preferences of a person and between groups </li></ul></ul><ul><ul><li>Considers thousands of people and thousand of items </li></ul></ul><ul><li>Personalized recommendations from databases based on similarities between the interest profile of the user and those of other users. </li></ul><ul><li>Ringo, makes personalized recommendations for music albums and artists. </li></ul><ul><li>As more people use the system, Ringo is able to make better predictions. </li></ul>
    11. 11. Agents <ul><li>Building Agents </li></ul><ul><ul><li>Two main problems </li></ul></ul><ul><ul><ul><li>Competence: how does an agent acquire knowledge? </li></ul></ul></ul><ul><ul><ul><li>Trust: how can the user feel comfortable delegating tasks to an agent? </li></ul></ul></ul><ul><ul><li>One approach (as used in Oval) is to make the end-user program the interface agent. This does not meet the competence criterion. </li></ul></ul><ul><ul><li>Another, the knowledge-based approach, gives the agent extensive background knowledge about the application and the user. Both competence and trust are problems in this approach. </li></ul></ul><ul><li>Use machine learning techniques </li></ul>
    12. 12. The Semantic Web <ul><li>An extension of the current Web, in which information is given well-defined meaning. </li></ul><ul><li>Computers must have access to structured collections of information. </li></ul><ul><li>XML and RDF </li></ul><ul><li>Ontologies </li></ul><ul><li>Digital signatures </li></ul>
    13. 13. KM on the Semantic Web <ul><li>Semantic Web can serve as a platform for developing knowledge management systems. </li></ul><ul><li>Problem: How to represent knowledge in a machine-understandable form, so that appropriate knowledge can be found by agents? </li></ul><ul><li>Use a conditional statement for the semantic annotation of knowledge sources. Statements used in the annotation can be put into the context of each other, which leads to efficient searching. </li></ul>
    14. 14. An Agent Based Approach to Knowledge Management <ul><li>MARS, a multiagent referral system for knowledge management </li></ul><ul><ul><li>MARS assigns an agent to each user </li></ul></ul><ul><ul><li>Agents facilitate their users’ interactions </li></ul></ul><ul><ul><li>Manage their personal social networks </li></ul></ul><ul><ul><li>Agents cooperate with one another </li></ul></ul>

    ×