A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2009; you can also visit the original URL.
The file type is application/pdf
.
Implementing relevance feedback in the Bayesian Network Retrieval model
2003
Journal of the American Society for Information Science and Technology
Relevance Feedback consists in automatically formulating a new query according to the relevance judgments provided by the user after evaluating a set of retrieved documents. In this article, we introduce several relevance feedback methods for the Bayesian Network Retrieval Model. The theoretical frame on which our methods are based uses the concept of partial evidences, which summarize the new pieces of information gathered after evaluating the results obtained by the original query. These
doi:10.1002/asi.10210
fatcat:goeekvjw5bdmzlmch4toj3wtyq