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Losee, R.M.: Browsing mixed structured and unstructured data (2006)
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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.
- Source
- Information processing and management. 42(2006) no.2, S.440-452
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Losee, R.M.: Determining information retrieval and filtering performance without experimentation (1995)
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- Date
- 22. 2.1996 13:14:10
- Source
- Information processing and management. 31(1995) no.4, S.555-572
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Losee, R.M.: Term dependence : truncating the Bahadur Lazarsfeld expansion (1994)
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- Source
- Information processing and management. 30(1994) no.2, S.293-303
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Losee, R.M.: ¬The effect of assigning a metadata or indexing term on document ordering (2013)
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- Abstract
- The assignment of indexing terms and metadata to documents, data, and other information representations is considered useful, but the utility of including a single term is seldom discussed. The author discusses a simple model of document ordering and then shows how assigning index and metadata labels improves or decreases retrieval performance. The Indexing and Metadata Advantage (IMA) factor measures how indexing or assigning a metadata term helps (or hurts) ordering performance. Performance values and the associated IMA expressions are computed, consistent with several different assumptions. The economic value associated with various term assignment decisions is developed. The IMA term advantage model itself is empirically validated with computer software that shows that the analytic results obtained agree completely with the actual performance gains and losses found when ordering all sets of 14 or fewer documents. When the formulas in the software are changed to differ from this model, the predictions of the actual performance are erroneous.
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Losee, R.M.: Text windows and phrases differing by discipline, location in document, and syntactic structure (1996)
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- Source
- Information processing and management. 32(1996) no.6, S.747-767
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Losee, R.M.: Improving collection browsing : small world networking and Gray code ordering (2017)
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- Abstract
- Documents in digital and paper libraries may be arranged, based on their topics, in order to facilitate browsing. It may seem intuitively obvious that ordering documents by their subject should improve browsing performance; the results presented in this article suggest that ordering library materials by their Gray code values and through using links consistent with the small world model of document relationships is consistent with improving browsing performance. Below, library circulation data, including ordering with Library of Congress Classification numbers and Library of Congress Subject Headings, are used to provide information useful in generating user-centered document arrangements, as well as user-independent arrangements. Documents may be linearly arranged so they can be placed in a line by topic, such as on a library shelf, or in a list on a computer display. Crossover links, jumps between a document and another document to which it is not adjacent, can be used in library databases to allow additional paths that one might take when browsing. The improvement that is obtained with different combinations of document orderings and different crossovers is examined and applications suggested.
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Losee, R.M.: Upper bounds for retrieval performance and their user measuring performance and generating optimal queries : can it get any better than this? (1994)
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- Source
- Information processing and management. 30(1994) no.2, S.193-203
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Haas, S.W.; Losee, R.M.: Looking in text windows : their size and composition (1994)
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- Source
- Information processing and management. 30(1994) no.5, S.619-629
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Losee, R.M.: Learning syntactic rules and tags with genetic algorithms for information retrieval and filtering : an empirical basis for grammatical rules (1996)
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- Source
- Information processing and management. 32(1996) no.2, S.185-197
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Losee, R.M.: Browsing document collections : automatically organizing digital libraries and hypermedia using the Gray code (1997)
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- Source
- Information processing and management. 33(1997) no.2, S.175-192
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Losee, R.M.: Decisions in thesaurus construction and use (2007)
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- Source
- Information processing and management. 43(2007) no.4, S.958-968
