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Information Retrieval

Published/Hosted by Springer. ISSN (printed): 1386-4564. ISSN (electronic): 1573-7659.

Information Retrieval is an international forum for theory and experiment in information retrieval and its application in the networked information environment. The journal will publish articles reporting substantial research results in a wide range of techniques applied to a variety of tasks and a variety of media including but not limited to: METHODS: Vector Space; Probabilistic Bayesian Logical Methods; Pattern Recognition; Signal Detection; Machine Learning; Natural Language; Semantic Structures: TASK DOMAINS : Classification; Evaluation; Indexing; Interaction; Retrieval; Routing; Filtering; Summarization; Synthesis: MEDIA : Text; Hypermedia; Static Images; Scientific Datasets; Sound; Moving Images; Multimedia; Multi-lingual; Distributed Systems. The ideal paper may be theoretical experimental or applied. A theoretical paper will report a significant conceptual advance in the design of algorithms or other processes for some information retrieval task. It will establish the validity or potential validity of the proposed ideas in terms of their relation to already accepted ideas and/or in terms of some modest prototype experiment or simulation. An experimental paper will report on a test of one or more theoretical ideas in a laboratory or natural setting. Experimental papers will be reviewed for both scientific and statistical merit and will be expected to discuss the limitations and generality of the reported results. An application paper will report the successful application of some already established technique to a significant real world problem involving information retrieval. Information Retrieval overlaps with a variety of technical and behavioral fields. Papers on such technical issues as compression and optimization and on issues of human behavior and cognition are appropriate insofar as they bear specifically on the issues of methods tasks or media as outlined above. Variations from these prototypes such as critical reviews of existing work and significant tutorials will be considered provided that they make a clear contribution to the field. Preference will be given to papers which unify concepts across several traditional disciplinary boundaries with specific application to problems of information retrieval.

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