Data processing: artificial intelligence – Knowledge processing system – Knowledge representation and reasoning technique
Reexamination Certificate
1999-08-24
2002-12-24
Black, Thomas (Department: 2121)
Data processing: artificial intelligence
Knowledge processing system
Knowledge representation and reasoning technique
C707S793000, C707S793000
Reexamination Certificate
active
06499024
ABSTRACT:
BACKGROUND OF THE INVENTION
This invention relates generally to knowledge management systems, and particularly to the development of knowledge base systems.
One environment in which knowledge management systems are particularly useful is the computer product support industry. The computer systems on today's desktops are complicated. They involve many products (hardware and software) from many vendors. The products may or may not operate as expected when configured into a system. In addition, the user guides and references for the products are often incomplete and not always accurate. When end users have problems with their computer systems, they often need help diagnosing and then solving the problem. The computer product support industry has developed in response to that need. When a caller into a technical support organization reports a problem with a product in a certain environment, a technical support representative, sometimes known as an agent, diagnoses and attempts to solve the problem.
However, a mountain of knowledge is necessary in order to provide support for computer products. End users' answers might be found in a public document, or in a customer's or vendor's confidential information, or in a company's bank of general or confidential knowledge. In addition, through support interactions, a company generates a vast array of knowledge, particularly in areas such as product interoperability. Knowledge is always being generated because the resolution to an end user's problem may even need to pieced together from many sources of information, public and private combined.
A computer product support provider's challenge is to handle the increasing technical complexity of support delivery while keeping service quality and customer satisfaction high and costs low. Companies must establish a support infrastructure that enable them to capture, refine, and publish customer service and support information with greater efficiency through a variety of support channels. Adopting a knowledge management approach is an effective means to meet urgent customer demands.
One part of the knowledge management approach is the development and maintenance of knowledge bases as a part of a company's knowledge management system. With the proliferation of information that is needed to run businesses today, many companies are turning to knowledge base systems to store and provide access to its information. Knowledge bases provide a framework for collecting, organizing and refining the full range of information that is both collected and generated daily by a company. Knowledge bases process the new information, transforming it into actionable knowledge, present it in a consistent format, and make it readily available. They make a company increasingly effective in gathering and leveraging “institutional memory.” Thus, knowledge bases provide a company with the opportunity to reuse the knowledge that it collects and creates. Such reuse is beneficial because it allows companies to use its data to conduct is business more quickly and efficiently than previously possible.
While knowledge bases provide some real benefit to companies that invest in their creation, they are expensive in time, resources and money to develop. Many complex issues must be addressed. For example, keeping in mind the work environment in which the knowledge base will operate, developers must decide the subject areas (known as domains) that would benefit from having knowledge about them incorporated into a knowledge base. They must select from which sources should the knowledge be obtained and the extent that an order in which the knowledge base should be seeded prior to activation. In addition, the developers must develop the knowledge base's architecture based on the information that it will hold and the use to which the knowledge will be put. They must develop operational processes for using the knowledge base and integrating it into with the other systems and processes used by the knowledge base user.
It is therefore an object to develop knowledge management systems that allow a company to manage the knowledge it collects and creates, make it available for use in conjunction with the other systems and processes used by the company, and monitor its use. It is a further object of this invention to develop and deploy a knowledge base so that it quickly contains a vast array of information. It is also an object to seamlessly integrate the knowledge base with the other systems and processes used by the knowledge base user, and develop operational processes for keeping the knowledge base updated.
SUMMARY OF THE INVENTION
In accordance with the present invention, there is described a method for creating a knowledge base. A baseline analysis is conducted of aspects of developing the knowledge base. At least one of the aspects is surveyed and a knowledge base complexity indicator is developed for each surveyed aspect. In the preferred embodiment, the complexity indicator involves an assessment of high, medium and low complexity of the aspect. In addition, a plurality of aspects are surveyed in the baseline analysis, and complexity indicators for the surveyed aspects are combined to give an overall knowledge base complexity indicator.
In the preferred embodiment, the base-line analysis is conducted in two stages. First, a high-level base-line analysis is conducted to provide an initial determination of the feasibility of developing the knowledge base and to identify costs for the developing, wherein an output of the high-level analysis is a project statement of work and a project cost estimate. If the high-level base-line analysis indicates that the developing is feasible, a full base-line analysis is conducted for each of the aspects.
The surveying results are input to an in-depth analysis, the outputs of which are a construction and seeding plan for the knowledge base, and specifications for operational processes. The specifications are for use of the knowledge base, for monitoring knowledge base operations, and for maintenance of the knowledge base.
In one embodiment, operational processes include a system for updating the knowledge base, a system for generating reports, knowledge base user and knowledge base author work flows, and knowledge base integration with systems or processes with which the knowledge base will interact or co-exist. Developing the specifications for operational processes involves conducting an integration analysis of the systems or processes with which the knowledge base will interact or co-exist, and developing specifications of a graphics user interface for the knowledge base based on an analysis of the knowledge base user and knowledge base author work flows.
Once the construction and seeding plan and operational processes specifications are developed, the knowledge base is developed by the sub-steps of constructing and seeding the knowledge base in accordance with the construction and seeding plan, developing the operational processes in accordance with the specifications for operational processes, and developing a deployment plan for deployment of the knowledge base and the operational processes. In the preferred embodiment, developing operational processes means developing software for a knowledge base user interface, for tool integration, and for reporting, and developing systems and processes for knowledge flow between the users and the authors, and between all of the beneficiaries of the use of the knowledge base. Also, developing the deployment plan involves developing schedules, resource allocation plans, pilot incentives, user documentation, and training.
Finally, the deployment is implemented by deploying the knowledge base and implementing the operational processes in accordance with the deployment plan. In one embodiment, implementing the operational processes further comprises compiling knowledge management metrics in order to monitor use of the knowledge base.
In one embodiment, conducting the in-depth analysis involves the steps of conducting a
Haughton Debra Ann
Stier Sharon
Black Thomas
Hirl Joseph P.
Moran Maura K.
Stream International, Inc.
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