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  • × author_ss:"Losee, R.M."
  • × language_ss:"e"
  1. Losee, R.M.: Browsing mixed structured and unstructured data (2006) 0.00 
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    Abstract
    Both structured and unstructured data, as well as structured data representing several different types of tuples, may be integrated into a single list for browsing or retrieval. Data may be arranged in the Gray code order of the features and metadata, producing optimal ordering for browsing. We provide several metrics for evaluating the performance of systems supporting browsing, given some constraints. Metadata and indexing terms are used for sorting keys and attributes for structured data, as well as for semi-structured or unstructured documents, images, media, etc. Economic and information theoretic models are suggested that enable the ordering to adapt to user preferences. Different relational structures and unstructured data may be integrated into a single, optimal ordering for browsing or for displaying tables in digital libraries, database management systems, or information retrieval systems. Adaptive displays of data are discussed.
    Type
    a
  2. Losee, R.M.: Comparing Boolean and probabilistic information retrieval systems across queries and disciplines (1997) 0.00 
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    Abstract
    Suggests a method for comparison of the use of Boolean queries and ranking documents using document and term weights, and examines their relative merits. The performance of information retrieval may be determined either by using experimental simulation, or through the application of analytic techniques that estimate the retrieval performance, given values for query and database characteristics. Using these performance predicting techniques, sample performance figures are provided for queries using the Boolean operators and, and or, as well as for probabilistic systems assuming statistical term independence or term dependence. Examines the performance of models failing to meet statistical and other assumptions
    Type
    a
  3. Losee, R.M.: How to study classification systems and their appropriateness for individual institutions (1995) 0.00 
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    Type
    a
  4. Losee, R.M.; Church Jr., L.: Are two document clusters better than one? : the cluster performance question for information retrieval (2005) 0.00 
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  5. Losee, R.M.: Learning syntactic rules and tags with genetic algorithms for information retrieval and filtering : an empirical basis for grammatical rules (1996) 0.00 
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    Type
    a

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