Data processing: artificial intelligence – Knowledge processing system
Reexamination Certificate
1999-08-17
2003-10-14
Starks, Jr., Wilbert L. (Department: 2122)
Data processing: artificial intelligence
Knowledge processing system
C707S793000, C707S793000
Reexamination Certificate
active
06633859
ABSTRACT:
The present invention relates to a knowledge-based system having an architecture that separates the presentation of information from its organization in the system.
BACKGROUND OF THE INVENTION
Knowledge-based systems, also known as “expert” systems, are typically application programs that make decisions or solve problems in a particular subject area, referred to as a “knowledge domain,” by using knowledge and analytical tools defined by experts in the field. By their very nature, expert systems are knowledge-intensive due to the goal of modeling human expertise in a domain. Such systems usually comprise two components: a knowledge base containing the information necessary to answer questions relevant to the domain and an inference engine to formulate answers to these questions, also known as “queries,” based on the information contained in the knowledge base. Also, a user interface typically is provided to receive the queries from either a user or another application program, to submit these queries to the inference engine, and then to provide responses back to the user or other application program.
Knowledge-based systems have been used in such diverse knowledge domains as engineering, the sciences, medicine, and business. Similar to numerical computer systems, they model situations and solve problems. However, and most importantly, knowledge-based systems also provide representation and reasoning capabilities that are not possible with most numerical methods. One specific example of this additional capability concerns the modeling of the knowledge possessed by human resource professionals in institutions, such as government agencies or commercial companies.
Human Resource (HR) departments currently use many systems to answer employee and managerial questions about employee benefit plans and HR policies, procedures, and practices. These questions include how to: use medical plans, take leaves of absence, and file harassment complaints, as well as other questions regarding, e.g., paycheck amounts.
The information sources used to answer these questions in the typical organization usually reside in various formal and informal repositories. Some sources are static documents, both paper and electronic. These documents, which may or may not have been generated by the department, are designed to answer questions posed by employees. Other information sources include dynamic databases, such as the human resource management systems (HRMS's) that contain accounting information for each employee. Finally, some information resides only in the heads of the experienced HR professionals in the organization. These various and unconnected systems are the basis of most companies' HR information dissemination processes today, but there are problems with the underlying model for information dissemination.
First, pre-prepared, static documents are costly to produce. These document types include manually maintained policy manuals, summary plan descriptions, and web sites. Second, these document types tend quickly to become dated, especially during major system or corporate reorganizations. Also, these resources often are able only to give general answers because many of the detailed answers vary depending on the particular employee's situation, eg., employee group, physical location, age, and length of employment.
In contrast, HRMSs, which are sometimes part of even larger enterprise resource planning systems (ERPs), contain vast quantities of accurate, constantly-updated data.
These dynamic systems, however, do not contain information such as HR policies or on how to submit forms. Thus, HRMSs tend to be able to answer very specific questions (e.g., what is the net amount on my monthly paycheck), but not general ones (e.g., I'm having a baby, what does the company do for me and what must I do to use these benefits).
Other systems, such as electronic collections of answers to questions previously asked by other employees, are easy to search, but require significant resources to prepare and still pose the same problems of prepared documents. These systems are also more likely to yield incorrect answers due to changes in policies or organization that would render previously correct answers incorrect. Not only is it tedious and difficult to identify and correct all of the affected answers following a change in policies or organization, it is even harder to verify that the changed answers are correct and complete. It quickly becomes apparent that such systems do not adequately address the deficiencies of other systems or satisfy the requirements of a useful information resource.
Finally, although HR professionals themselves can be used to answer questions, this resource is both expensive and inefficient. Using HR professionals to constantly answer repetitive questions, instead of working on more strategic initiatives, is not the best application of their skills and may result in the loss of talented HR professionals from the organization. In addition, finding the right knowledgeable person to answer a question can be a frustrating and slow process for an employee. Furthermore, such resources may not be accessed by other applications. Thus, relying on HR personnel to provide employee information is not a viable option for any but the smallest of organizations.
Consequently, knowledge modeling and delivery systems have evolved that combine pre-configured, parameterized models of human resource knowledge with organization and employee data. Such expert systems have successfully delivered personalized answers to employee and manager questions about benefit plans, payroll, HR policies, procedures, and practices using expert system inferencing techniques.
However, in the advancement of knowledge systems generally, most of the effort has been directed to improving knowledge modeling and inferencing techniques to improve reliability and the value of the information they provide to the user. Unfortunately, because of the limited commercial viability of these techniques thus far, insufficient effort has been expended to improve the delivery of information generated by the knowledge system to the user. However, if such knowledge-based systems are ever to be deployed more generally, issues such as information presentation move to the forefront.
In the past, knowledge-based systems have generally employed one or two means to present the information drawn by the inferencing engine from the knowledge base. Most commonly, presentation of the information is dependent on how the knowledge in the knowledge base is organized. Domain experts mentally inevitably organize their knowledge differently from how various potential users might like to retrieve it. Thus, the domain experts often design and build a knowledge model of a domain that matches their mental organization of the domain, while different users of the model want to see the information contained in the model using different organizations. The typical solution—providing general and technical levels of responses—does not adequately meet anyone's information needs in most situations.
Recently, however, efforts have been focused on separating how the information is displayed from how it is stored in the knowledge base in order to present the same information in a variety of ways. However, improvements still can be made in how information is presented to the user. Problems continue to arise due to the fact that a given user's needs may vary based on the nature of the information required.
Returning to the specific example of expert systems that address HR-related questions, it is not uncommon for an HR functional expert to create a presentation, such as a Web site or manual, that describes a particular policy or benefit plan. While the information presented seems to be complete and correct to the HR functional expert, when the presentation is referenced by an employee with a specific problem or question regarding the plan or policy, the information is often very difficult to digest. The information may be perceived by the employee as be
Barnes-Guzman Didier
Farlow Timothy S.
Silva Daniel
Authoria, Inc.
Starks, Jr. Wilbert L.
LandOfFree
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