Search (23 results, page 1 of 2)

Losee, R.M.: Determining information retrieval and filtering performance without experimentation (1995) 0.03

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Date: 22. 2.1996 13:14:10
Source: Information processing and management. 31(1995) no.4, S.555-572

Losee, R.M.: Term dependence : truncating the Bahadur Lazarsfeld expansion (1994) 0.02

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Source: Information processing and management. 30(1994) no.2, S.293-303

Losee, R.M.: Browsing mixed structured and unstructured data (2006) 0.01
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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

Losee, R.M.: ¬The science of information : measurement and applications (1990) 0.01

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COMPASS: Information science
Series: Library and information science
Subject: Information science

Losee, R.M.: Text windows and phrases differing by discipline, location in document, and syntactic structure (1996) 0.01

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Source: Information processing and management. 32(1996) no.6, S.747-767

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) 0.01

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Source: Information processing and management. 30(1994) no.2, S.193-203

Haas, S.W.; Losee, R.M.: Looking in text windows : their size and composition (1994) 0.01

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Source: Information processing and management. 30(1994) no.5, S.619-629

Losee, R.M.: Learning syntactic rules and tags with genetic algorithms for information retrieval and filtering : an empirical basis for grammatical rules (1996) 0.01

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Source: Information processing and management. 32(1996) no.2, S.185-197

Losee, R.M.: Browsing document collections : automatically organizing digital libraries and hypermedia using the Gray code (1997) 0.01

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Source: Information processing and management. 33(1997) no.2, S.175-192

Losee, R.M.: Decisions in thesaurus construction and use (2007) 0.01

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Source: Information processing and management. 43(2007) no.4, S.958-968

Losee, R.M.; Paris, L.A.H.: Measuring search-engine quality and query difficulty : ranking with Target and Freestyle (1999) 0.01

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Source: Journal of the American Society for Information Science. 50(1999) no.10, S.882-889

Losee, R.M.: Seven fundamental questions for the science of library classification (1993) 0.01

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Abstract: For classification to advance to the point where optimal systems may be developed for manual or automated use, it will be necessary for a science of document or library classification to be developed. Seven questions are posed which the author feels must be answered before such optimal systems can be developed. Suggestions are made as to the forms that answers to these questions might take

Losee, R.M.; Haas, S.W.: Sublanguage terms : dictionaries, usage, and automatic classification (1995) 0.01
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Abstract

The use of terms from natural and social science titles and abstracts is studied from the perspective of sublanguages and their specialized dictionaries. Explores different notions of sublanguage distinctiveness. Object methods for separating hard and soft sciences are suggested based on measures of sublanguage use, dictionary characteristics, and sublanguage distinctiveness. Abstracts were automatically classified with a high degree of accuracy by using a formula that condsiders the degree of uniqueness of terms in each sublanguage. This may prove useful for text filtering of information retrieval systems

Source

Journal of the American Society for Information Science. 46(1995) no.7, S.519-529

Spink, A.; Losee, R.M.: Feedback in information retrieval (1996) 0.00

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Source: Annual review of information science and technology. 31(1996), S.33-78

Losee, R.M.: ¬A discipline independent definition of information (1997) 0.00

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Source: Journal of the American Society for Information Science. 48(1997) no.3, S.254-269

Losee, R.M.: ¬A Gray code based ordering for documents on shelves : classification for browsing and retrieval (1992) 0.00

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Source: Journal of the American Society for Information Science. 43(1992) no.4, S.312-322

Losee, R.M.: Comparing Boolean and probabilistic information retrieval systems across queries and disciplines (1997) 0.00

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Source: Journal of the American Society for Information Science. 48(1997) no.2, S.143-156

Losee, R.M.: When information retrieval measures agree about the relative quality of document rankings (2000) 0.00

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Source: Journal of the American Society for Information Science. 51(2000) no.9, S.834-840

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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Source: Journal of the American Society for Information Science and Technology. 56(2005) no.1, S.106-108

Losee, R.M.: Evaluating retrieval performance given database and query characteristics : analytic determination of performance surfaces (1996) 0.00

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Source: Journal of the American Society for Information Science. 47(1996) no.1, S.95-105

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