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Browse Prior Art Database

Knowledge Management on Computer Systems

IP.com Disclosure Number: IPCOM000016378D
Original Publication Date: 2002-Oct-03
Included in the Prior Art Database: 2003-Jun-21
Document File: 5 page(s) / 48K

Publishing Venue

IBM

Abstract

While managing knowledge among people is something mankind has learned over the millennia, managing knowledge between people and computers is far from being understood. The bottleneck is the computer, or more precisely, the way knowledge is currently managed on computer systems and the way humans communicate with them. An appropriate model for representing knowledge is required if one wants to avoid losing most of its content when transferring it into an explicit form. Thus, models for representing, acquiring, and using explicit knowledge are one essential requirement for successfully managing knowledge. Such a model general and representing a meaning recognition system in particular is disclosed in the PCT Patent Application WO 99/63455 and the European Patent Application EP 1 213 660 A2. Furthermore, understanding the way people interact and communicate with computer systems is of equal importance. Today standard computers are replaced with personal pervasive computing devices. Services provided on these devices enable the user to carry out his desired tasks from virtually anywhere. These services can now be personalized to their users since they are carried out on personal devices. Personalization is achieved by enriching a service with a portion of a user’s personal tacit knowledge, which consists of a user’s preferences with respect to the service, his current context, and some more general background knowledge about the user. Thus, through this shared knowledge between the user and the service, interaction is greatly simplified. In fact, by using a good model to represent the personalization knowledge the service can be provided in such a way that the user almost appears to talk to his alter ego. This level of communication between human and machine is another essential requirement for successfully managing knowledge when dealing with a mixed environment of people and computers. As an example, an intelligent personal phone book service is proposed which can be offered on a cell phone. The knowledge about phone numbers for people, groups, places, etc. is represented in a model based on active semantic networks, as explained in detail in the above mentioned patent applications. This model can offer the advantages of both representing knowledge similar to the way people think and allowing a natural way of communication between the user and the system. The latter advantage is even amplified through the personalization or the service since this makes the communication even more natural by enabling the user to request a phone connection by referring to his personal tacit knowledge. The service personalization is carried out by an automatic learning mechanism which allows the system to automatically acquire appropriate pieces of the user’s tacit knowledge into his ‘personalization knowledge’, provided the system is confronted with this knowledge through some form of interaction. An example of a user query is "Please connect me to that person from my bank to whom I spoke yesterday about my car loan." Artificial intelligence sub disciplines of cognitive modeling and knowledge representation can help with the task of managing any form of organizational knowledge. Specifically,

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Knowledge Management on Computer Systems

  While managing knowledge among people is something mankind has learned over the millennia, managing knowledge between people and computers is far from being understood. The bottleneck is the computer, or more precisely, the way knowledge is currently managed on computer systems and the way humans communicate with them. An appropriate model for representing knowledge is required if one wants to avoid losing most of its content when transferring it into an explicit form. Thus, models for representing, acquiring, and using explicit knowledge are one essential requirement for successfully managing knowledge. Such a model general and representing a meaning recognition system in particular is disclosed in the PCT Patent Application WO 99/63455 and the European Patent Application EP 1 213 660 A2.

Furthermore, understanding the way people interact and communicate with computer systems is of equal importance. Today standard computers are replaced with personal pervasive computing devices. Services provided on these devices enable the user to carry out his desired tasks from virtually anywhere. These services can now be personalized to their users since they are carried out on personal devices. Personalization is achieved by enriching a service with a portion of a user's personal tacit knowledge, which consists of a user's preferences with respect to the service, his current context, and some more general background knowledge about the user. Thus, through this shared knowledge between the user and the service, interaction is greatly simplified. In fact, by using a good model to represent the personalization knowledge the service can be provided in such a way that the user almost appears to talk to his alter ego. This level of communication between human and machine is another essential requirement for successfully managing knowledge when dealing with a mixed environment of people and computers.

As an example, an intelligent personal phone book service is proposed which can be offered on a cell phone. The knowledge about phone numbers for people, groups, places, etc. is represented in a model based on active semantic networks, as explained in detail in the above mentioned patent applications. This model can offer the advantages of both representing knowledge similar to the way people think and allowing a natural way of communication between the user and the system. The latter advantage is even amplified through the personalization or the service since this makes the communication even more natural by enabling the user to request a phone connection by referring to his personal tacit knowledge. The service personalization is carried out by an automatic learning mechanism which allows the system to automatically acquire appropriate pieces of the user's tacit knowledge into his 'personalization knowledge', provided the system is confronted with this knowledge through some form of interaction. An example o...