-
Losee, R.M.: Term dependence : a basis for Luhn and Zipf models (2001)
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- Abstract
- There are regularities in the statistical information provided by natural language terms about neighboring terms. We find that when phrase rank increases, moving from common to less common phrases, the value of the expected mutual information measure (EMIM) between the terms regularly decreases. Luhn's model suggests that midrange terms are the best index terms and relevance discriminators. We suggest reasons for this principle based on the empirical relationships shown here between the rank of terms within phrases and the average mutual information between terms, which we refer to as the Inverse Representation- EMIM principle. We also suggest an Inverse EMIM term weight for indexing or retrieval applications that is consistent with Luhn's distribution. An information theoretic interpretation of Zipf's Law is provided. Using the regularity noted here, we suggest that Zipf's Law is a consequence of the statistical dependencies that exist between terms, described here using information theoretic concepts.
- Source
- Journal of the American Society for Information Science and technology. 52(2001) no.12, S.1019-1025
-
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.
- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.11, S.2191-2200
-
Losee, R.M.: ¬The science of information : measurement and applications (1990)
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- COMPASS
- Information science
- Series
- Library and information science
- Subject
- Information science
-
Losee, R.M.; Paris, L.A.H.: Measuring search-engine quality and query difficulty : ranking with Target and Freestyle (1999)
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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)
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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)
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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
-
Losee, R.M.: Decisions in thesaurus construction and use (2007)
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- Abstract
- A thesaurus and an ontology provide a set of structured terms, phrases, and metadata, often in a hierarchical arrangement, that may be used to index, search, and mine documents. We describe the decisions that should be made when including a term, deciding whether a term should be subdivided into its subclasses, or determining which of more than one set of possible subclasses should be used. Based on retrospective measurements or estimates of future performance when using thesaurus terms in document ordering, decisions are made so as to maximize performance. These decisions may be used in the automatic construction of a thesaurus. The evaluation of an existing thesaurus is described, consistent with the decision criteria developed here. These kinds of user-focused decision-theoretic techniques may be applied to other hierarchical applications, such as faceted classification systems used in information architecture or the use of hierarchical terms in "breadcrumb navigation".
-
Spink, A.; Losee, R.M.: Feedback in information retrieval (1996)
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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)
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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)
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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)
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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)
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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)
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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.: Determining information retrieval and filtering performance without experimentation (1995)
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- Date
- 22. 2.1996 13:14:10
-
Losee, R.M.: Evaluating retrieval performance given database and query characteristics : analytic determination of performance surfaces (1996)
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- Source
- Journal of the American Society for Information Science. 47(1996) no.1, S.95-105
-
Willis, C.; Losee, R.M.: ¬A random walk on an ontology : using thesaurus structure for automatic subject indexing (2013)
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- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.7, S.1330-1344
