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Titlebook: Soft Computing in Information Retrieval; Techniques and Appli Fabio Crestani,Gabriella Pasi Book 2000 Physica-Verlag Heidelberg 2000 Bayesi

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The Java Search Agent Workshopnd implementation status, we present several sample Java implementations including a best first search spider and G-Search spider for Internet searching, and a Hopfield neural network based visualizer for database searching. Lessons learned and future directions are also presented.
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Probabilistic Learning by Uncertainty Sampling with Non-Binary Relevance uncertainty sampling by considering multiple levels of relevance and we show how this new learning model for information retrieval and filtering could be evaluated using collections with non-binary relevance assessments.
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A Framework for Linguistic and Hierarchical Queries in Document Retrievaltrieve. This language allows for a specification of the interrelationship between the desired attributes using linguistic quantifiers. This framework also supports a hier-archical formulation of queries. These features allow for an increased expressiveness in the queries that be handled by a retriev
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A Model of Intelligent Information Retrieval Using Fuzzy Tolerance Relations Based on Hierarchical Cclude the actual words that occur in the documents that should be retrieved. Fuzzy tolerance and similarity relations will be presented and the notion of hierarchical co-occurrence is defined that allows the introduction of two or more hierarchical categories of words in the documents. If the query
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Visual Keywords: from Text Retrieval to Multimedia Retrievaleaningful semantics to users, can be extracted relatively easily from text docu-ments. In the case of visual contents which are perceptual in nature, the definition of corresponding “keywords” and automatic extraction are unclear and non-trivial. Is there a similar metaphor or mechanism for visual d
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Document Classification with Unsupervised Artificial Neural Networksve to perform on text documents are classification tasks based on noisy patterns. In particular we rely on self-organizing maps which produce a map of the document space after their training process. From geography, however, it is known that maps are not always the best way to represent information
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