Name
Abstract | ||
|---|---|---|
We consider a new variety of sequential information gathering problems that are applicable for Web-based applications in which data provided as input may be distorted by the system user, such as an applicant for a credit card. We propose two methods to compensate for input distortion. The first method, termedknowledge base modification, considers redesigning the knowledge base of an expert system to best account for distortion in the input provided by the user. The second method, termedinput modification, modifies the input directly to account for distortion and uses the modified input in the existing (unmodified) knowledge base of the system. These methods are compared with an approach where input noise is ignored. Experimental results indicate that both types of modification substantially improve the accuracy of recommendations, with knowledge base modification outperforming input modification in most cases. Knowledge base modification is, however, more computationally intensive than input modification. Therefore, when computational resources are adequate, the knowledge base modification approach is preferred; when such resources are very limited, input modification may be the only viable alternative. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1287/isre.1050.0046 | Information Systems Research |
Keywords | Field | DocType |
input distortion,h. r. rao,2004,expert systems,and was with the authors 5 months for 2 revisions.,noise handling history: salvatore march,modified input,knowledge base modification,expert systems redesign,termedinput modification,termedknowledge base modification,expert system,sequential information gathering,knowledge base,knowledge base modification approach,associate editor. this paper was received on february 13,input modification,senior editor,input noise,web based applications | Data mining,World Wide Web,Computer science,Lying,Expert system,Knowledge management,Credit card,Knowledge base,Distortion | Journal |
Volume | Issue | ISSN |
16 | 2 | 1047-7047 |
Citations | PageRank | References |
11 | 0.60 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhengrui Jiang | 1 | 80 | 10.69 |
| Vijay S. Mookerjee | 2 | 470 | 196.94 |
| Sumit Sarkar | 3 | 835 | 260.90 |