Search (17 results, page 1 of 1)

  • × author_ss:"Losee, R.M."
  • × year_i:[1990 TO 2000}
  1. Losee, R.M.: Determining information retrieval and filtering performance without experimentation (1995) 0.03 
    0.02713491 = product of:
  0.05426982 = sum of:
    0.05426982 = sum of:
      0.010589487 = weight(_text_:a in 3368) [ClassicSimilarity], result of:
        0.010589487 = score(doc=3368,freq=10.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.19940455 = fieldWeight in 3368, product of:
            3.1622777 = tf(freq=10.0), with freq of:
              10.0 = termFreq=10.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.0546875 = fieldNorm(doc=3368)
      0.043680333 = weight(_text_:22 in 3368) [ClassicSimilarity], result of:
        0.043680333 = score(doc=3368,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.2708308 = fieldWeight in 3368, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0546875 = fieldNorm(doc=3368)
  0.5 = coord(1/2)
    Abstract
    The performance of an information retrieval or text and media filtering system may be determined through analytic methods as well as by traditional simulation or experimental methods. These analytic methods can provide precise statements about expected performance. They can thus determine which of 2 similarly performing systems is superior. For both a single query terms and for a multiple query term retrieval model, a model for comparing the performance of different probabilistic retrieval methods is developed. This method may be used in computing the average search length for a query, given only knowledge of database parameter values. Describes predictive models for inverse document frequency, binary independence, and relevance feedback based retrieval and filtering. Simulation illustrate how the single term model performs and sample performance predictions are given for single term and multiple term problems
    Date
    22. 2.1996 13:14:10
    Type
    a
  2. Losee, R.M.: ¬A Gray code based ordering for documents on shelves : classification for browsing and retrieval (1992) 0.00 
    0.00334869 = product of:
  0.00669738 = sum of:
    0.00669738 = product of:
      0.01339476 = sum of:
        0.01339476 = weight(_text_:a in 2335) [ClassicSimilarity], result of:
          0.01339476 = score(doc=2335,freq=16.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.25222903 = fieldWeight in 2335, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2335)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    A document classifier places documents together in a linear arrangement for browsing or high-speed access by human or computerised information retrieval systems. Requirements for document classification and browsing systems are developed from similarity measures, distance measures, and the notion of subject aboutness. A requirement that documents be arranged in decreasing order of similarity as the distance from a given document increases can often not be met. Based on these requirements, information-theoretic considerations, and the Gray code, a classification system is proposed that can classifiy documents without human intervention. A measure of classifier performance is developed, and used to evaluate experimental results comparing the distance between subject headings assigned to documents given classifications from the proposed system and the Library of Congress Classification (LCC) system
    Type
    a
  3. Losee, R.M.: ¬The relative shelf location of circulated books : a study of classification, users, and browsing (1993) 0.00 
    0.0031324127 = product of:
  0.0062648254 = sum of:
    0.0062648254 = product of:
      0.012529651 = sum of:
        0.012529651 = weight(_text_:a in 4485) [ClassicSimilarity], result of:
          0.012529651 = score(doc=4485,freq=14.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.23593865 = fieldWeight in 4485, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4485)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    Patrons often browse through books organized by a library classification system, looking for books to use and possibly circulate. This research is an examination of the clustering of similar books provided by a classification system and ways in which the books that patrons circulate are clustered. Measures of classification system performance are suggested and used to evaluate two test collections. Regression formulas are derived describing the relationships among the number of areas in which books were found (the number of stops a patron makes when browsing), the distances across a cluster, and the average number of books a patron circulates. Patrons were found usually to make more stops than there were books found at their average stop. Consequences for full-text document systems and online catalogs are suggested
    Type
    a
  4. Losee, R.M.: ¬A discipline independent definition of information (1997) 0.00 
    0.0030255679 = product of:
  0.0060511357 = sum of:
    0.0060511357 = product of:
      0.012102271 = sum of:
        0.012102271 = weight(_text_:a in 380) [ClassicSimilarity], result of:
          0.012102271 = score(doc=380,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.22789092 = fieldWeight in 380, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=380)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    Information may be defined as the characteristics of the output of a process, these being informative about the process and the input. This discipline independent definition may be applied to all domains, from physics to epistemology. Hierarchies of processes linked together, provide a communication channel between each of the corresponding functions and layers in the hierarchies. Models of communication, perception, observation, belief, and knowledge are suggested that are consistent with this conceptual framework of information as the value of the output of any process in a hierarchy of processes. Misinformation and errors are considered
    Type
    a
  5. 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) 0.00 
    0.0024857575 = product of:
  0.004971515 = sum of:
    0.004971515 = product of:
      0.00994303 = sum of:
        0.00994303 = weight(_text_:a in 7418) [ClassicSimilarity], result of:
          0.00994303 = score(doc=7418,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18723148 = fieldWeight in 7418, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=7418)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    The best-case, random and worst-case document rankings and retrieval performance may be determined using a method discussed here. Knowledge of the best case performance allows users and system designers to determine how close to the optimum condition their search is and select queries and matching functions that will produce the best results. Suggests a method for deriving the optimal Boolean query for a given level of recall and a method for determining the quality of a Boolean query. Measures are proposed that modify conventional text retrieval measures such as precision, E, and average search length, so that the values for these measures are 1 when retrieval is optimal, 0 when retrieval is random, and -1 when worst-case. Tests using one of these measures show that many retrieval are optimal? Consequences for retrieval research are examined
    Type
    a
  6. Losee, R.M.: Evaluating retrieval performance given database and query characteristics : analytic determination of performance surfaces (1996) 0.00 
    0.0024857575 = product of:
  0.004971515 = sum of:
    0.004971515 = product of:
      0.00994303 = sum of:
        0.00994303 = weight(_text_:a in 4162) [ClassicSimilarity], result of:
          0.00994303 = score(doc=4162,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18723148 = fieldWeight in 4162, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=4162)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    An analytic method of information retrieval and filtering evaluation can quantitatively predict the expected number of documents examined in retrieving a relevant document. It also allows researchers and practioners to qualitatively understand how varying different estimates of query parameter values affects retrieval performance. The incoorporation of relevance feedback to increase our knowledge about the parameters of relevant documents and the robustness of parameter estimates is modeled. Single term and two term independence models, as well as a complete term dependence model, are developed. An economic model of retrieval performance may be used to study the effects of database size and to provide analytic answers to questions comparing retrieval from small and large databases, as well as questions about the number of terms in a query. Results are presented as a performance surface, a three dimensional graph showing the effects of two independent variables on performance.
    Type
    a
  7. Losee, R.M.: Text windows and phrases differing by discipline, location in document, and syntactic structure (1996) 0.00 
    0.0023678814 = product of:
  0.0047357627 = sum of:
    0.0047357627 = product of:
      0.009471525 = sum of:
        0.009471525 = weight(_text_:a in 6962) [ClassicSimilarity], result of:
          0.009471525 = score(doc=6962,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17835285 = fieldWeight in 6962, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6962)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    Knowledge of window style, content, location, and grammatical structure may be used to classify documents as originating within a particular discipline or may be used to place a document on a theory vs. practice spectrum. Examines characteristics of phrases and text windows, including their number, location in documents, and grammatical construction, in addition to studying variations in these window characteristics across disciplines. Examines some of the linguistic regularities for individual disciplines, and suggests families of regularities that may provide helpful for the automatic classification of documents, as well as for information retrieval and filtering applications
    Type
    a
  8. Losee, R.M.; Haas, S.W.: Sublanguage terms : dictionaries, usage, and automatic classification (1995) 0.00 
    0.0023435948 = product of:
  0.0046871896 = sum of:
    0.0046871896 = product of:
      0.009374379 = sum of:
        0.009374379 = weight(_text_:a in 2650) [ClassicSimilarity], result of:
          0.009374379 = score(doc=2650,freq=6.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17652355 = fieldWeight in 2650, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=2650)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    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
    Type
    a
  9. Haas, S.W.; Losee, R.M.: Looking in text windows : their size and composition (1994) 0.00 
    0.002269176 = product of:
  0.004538352 = sum of:
    0.004538352 = product of:
      0.009076704 = sum of:
        0.009076704 = weight(_text_:a in 8525) [ClassicSimilarity], result of:
          0.009076704 = score(doc=8525,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.1709182 = fieldWeight in 8525, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=8525)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    A text window is a group of words appearing in contiguous positions in text used to exploit a variety of lexical, syntactics, and semantic relationships without having to analyze the text explicitely for their structure. This supports the previously suggested idea that natural grouping of words are best treated as a unit of size 7 to 11 words, that is, plus or minus 3 to 5 words. The text retrieval experiments varying the size of windows, both with full text and with stopwords removed, support these size ranges. The characteristcs of windows that best match terms in queries are examined in detail, revealing intersting differences between those for queries with good results and those for queries with poorer results. Queries with good results tend to contain morte content word phrase and few terms with high frequency of use in the database. Information retrieval systems may benefit from expanding thesaurus-style relationships or incorporating statistical dependencies for terms within these windows
    Type
    a
  10. Losee, R.M.: Term dependence : truncating the Bahadur Lazarsfeld expansion (1994) 0.00 
    0.0020296127 = product of:
  0.0040592253 = sum of:
    0.0040592253 = product of:
      0.008118451 = sum of:
        0.008118451 = weight(_text_:a in 7390) [ClassicSimilarity], result of:
          0.008118451 = score(doc=7390,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.15287387 = fieldWeight in 7390, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.09375 = fieldNorm(doc=7390)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Type
    a
  11. Losee, R.M.; Paris, L.A.H.: Measuring search-engine quality and query difficulty : ranking with Target and Freestyle (1999) 0.00 
    0.0020296127 = product of:
  0.0040592253 = sum of:
    0.0040592253 = product of:
      0.008118451 = sum of:
        0.008118451 = weight(_text_:a in 4310) [ClassicSimilarity], result of:
          0.008118451 = score(doc=4310,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.15287387 = fieldWeight in 4310, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.09375 = fieldNorm(doc=4310)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Type
    a
  12. Losee, R.M.: Seven fundamental questions for the science of library classification (1993) 0.00 
    0.001913537 = product of:
  0.003827074 = sum of:
    0.003827074 = product of:
      0.007654148 = sum of:
        0.007654148 = weight(_text_:a in 4508) [ClassicSimilarity], result of:
          0.007654148 = score(doc=4508,freq=4.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.14413087 = fieldWeight in 4508, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=4508)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    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
    Type
    a
  13. Spink, A.; Losee, R.M.: Feedback in information retrieval (1996) 0.00 
    0.001913537 = product of:
  0.003827074 = sum of:
    0.003827074 = product of:
      0.007654148 = sum of:
        0.007654148 = weight(_text_:a in 7441) [ClassicSimilarity], result of:
          0.007654148 = score(doc=7441,freq=4.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.14413087 = fieldWeight in 7441, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=7441)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Type
    a
  14. Losee, R.M.: Browsing document collections : automatically organizing digital libraries and hypermedia using the Gray code (1997) 0.00 
    0.001757696 = product of:
  0.003515392 = sum of:
    0.003515392 = product of:
      0.007030784 = sum of:
        0.007030784 = weight(_text_:a in 146) [ClassicSimilarity], result of:
          0.007030784 = score(doc=146,freq=6.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.13239266 = fieldWeight in 146, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=146)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Abstract
    Relevance and economic feedback may be used to produce an ordering of documents that supports browsing in hypermedia and digital libraries. Document classification based on the Gray code provides paths through the entire collection, each path traversing each node in the set of documents exactly once. Examines systems organizing document based on weighted and unweighted Gray codes. Relevance feedback is used to conceptually organize the collection for an individual to browse, based on that individual's interests and information needs, as reflected by their relevance judgements and user supplied economic preferences. Applies Bayesian learning theory to estimating the characteristics of documents of interest to the user and supplying an analytic model of browsing performance, based on minimising the Expected Browsing Distance. Economic feedback may be used to change the ordering of documents to benefit the user. Using these techniques, a hypermedia or digital library may order any and all available documents, not just those examined, based on the information provided by the searcher or people with similar interests
    Footnote
    Contribution to a special issue on methods and tools for the automatic construction of hypertext
    Type
    a
  15. Losee, R.M.: Comparing Boolean and probabilistic information retrieval systems across queries and disciplines (1997) 0.00 
    0.001674345 = product of:
  0.00334869 = sum of:
    0.00334869 = product of:
      0.00669738 = sum of:
        0.00669738 = weight(_text_:a in 7709) [ClassicSimilarity], result of:
          0.00669738 = score(doc=7709,freq=4.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.12611452 = fieldWeight in 7709, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=7709)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    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
  16. Losee, R.M.: How to study classification systems and their appropriateness for individual institutions (1995) 0.00 
    0.001353075 = product of:
  0.00270615 = sum of:
    0.00270615 = product of:
      0.0054123 = sum of:
        0.0054123 = weight(_text_:a in 5545) [ClassicSimilarity], result of:
          0.0054123 = score(doc=5545,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.10191591 = fieldWeight in 5545, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=5545)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Type
    a
  17. 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 
    0.0010148063 = product of:
  0.0020296127 = sum of:
    0.0020296127 = product of:
      0.0040592253 = sum of:
        0.0040592253 = weight(_text_:a in 4068) [ClassicSimilarity], result of:
          0.0040592253 = score(doc=4068,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.07643694 = fieldWeight in 4068, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=4068)
      0.5 = coord(1/2)
  0.5 = coord(1/2)
    Type
    a

Authors

Themes