Examines the statistical distribution of relevance judgments by reviewing and comparing the results of several studies over the last three decades. A characteristic distribution is examined, and a hypothesis is offered to explain it based on human judging characteristics and the nature of relevance experimentation. (Contains 13 references.) (LRW)

Presents a coordination level matching algorithm to be used in document retrieval systems that incorporate relevance feedback strategies. It is argued that this algorithm may eliminate the need for the frequent reevaluation of documents that is currently found in such systems, and conditions under which reranking is unnecessary are given.…

Describes probabilistic document retrieval systems as a sequential learning process, in which the system learns the parameters of probability distributions describing the frequencies of feature occurrences in relevant and nonrelevant documents. Several techniques for estimating the parameters of distributions are described and the results of tests…

Describes a document retrieval system that provides for user interaction at several search stages to acquire a detailed specification of the user's information need. The use of domain knowledge to refine the query and a browsing mechanism are described in detail, and further research questions are identified. (CLB)