Article Efficient processing of vague queries using a data stream approach Share on Authors: Ulrich Pfeifer University of Dortmund, Germany University of Dortmund, GermanyView Profile , Norbert Fuhr University of Dortmund, Germany University of Dortmund, GermanyView Profile Authors Info & Claims SIGIR '95: Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrievalJuly 1995 Pages 189–197https://doi.org/10.1145/215206.215359Online:01 July 1995Publication History 6citation320DownloadsMetricsTotal Citations6Total Downloads320Last 12 Months3Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

We show that former approaches in probabilistic information retrieval are based on one or two of the three concepts abstraction, inductive learning , and probabilistic assumptions , and we propose a new approach which combines all three concepts. This approach is illustrated for the case of indexing with a controlled vocabulary. For this purpose, we describe a new probabilistic model first, which is then combined with logistic regression, thus yielding a generalization of the original model. Experimental results for the pure theoretical model as well as for heuristic variants are given. Furthermore, linear and logistic regression are compared.

We distinguish model-oriented and description-oriented approaches in probabilistic information retrieval.The former refer to certain representations of documents and