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Probabilistic Learning for Selective Dissemination of Information.
Peer reviewed Peer reviewed
Amati, Gianni; Crestani, Fabio – Information Processing & Management, 1999
Describes and evaluates a learning model for information filtering and selective dissemination of information which is an adaptation of the generalized probabilistic model of information retrieval. The model is based on the concept of uncertainty sampling that allows for relevance feedback both on relevant and nonrelevant documents. (Author/LRW)
Descriptors: Evaluation Methods, Feedback, Information Retrieval, Learning Processes
Data Discretization for Novel Relationship Discovery in Information Retrieval.
Peer reviewed Peer reviewed
Benoit, G. – Journal of the American Society for Information Science and Technology, 2002
Describes an information retrieval, visualization, and manipulation model which offers the user multiple ways to exploit the retrieval set, based on weighted query terms, via an interactive interface. Outlines the mathematical model and describes an information retrieval application built on the model to search structured and full-text files.…
Descriptors: Computer Interfaces, Information Retrieval, Mathematical Formulas, Mathematical Models