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Information Storage and… | 64 |
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Kemp, D. A. – Information Storage and Retrieval, 1974
The difference between pertinence and relevance is discussed. Other pairs of terms and the differences between their members are examined, and the suggestion is made that such studies could increase our understanding of the theory of information systems, and thence lead to practical improvements. (Author)
Descriptors: Information Retrieval, Information Systems, Relevance (Information Retrieval)
Heine, M. H. – Information Storage and Retrieval, 1973
The Marczewski-Steinhaus metric provides what appears to be an objective general measure of retrieval effectiveness within the framework of set theory and the theory of metric spaces. (19 references) (Author/SJ)
Descriptors: Information Retrieval, Relevance (Information Retrieval), Set Theory
Foskett, D. J. – Information Storage and Retrieval, 1972
The author distinguished between relevance and pertinence as applied to information retrieval. (6 references) (SJ)
Descriptors: Information Needs, Information Retrieval, Relevance (Information Retrieval)
Farradane, J.; And Others – Information Storage and Retrieval, 1973
The use of a structured system of storing information, particularly relational indexing, can lead to situations in which items would not be retrieved due to technicalities of the system. To overcome such problems a study was made of condensations with the aim of providing a series of rules to apply. (4 references) (Author/SJ)
Descriptors: Indexing, Information Retrieval, Information Storage, Relevance (Information Retrieval)
Salton, G. – Information Storage and Retrieval, 1973
The SMART system is used for the analysis, search and retrieval of news stories appearing in Time'' magazine. A comparison is made between the automatic text processing methods incorporated into the SMART system and a manual search using the classified index to Time.'' (14 references) (Author)
Descriptors: Current Events, Information Retrieval, Periodicals, Relevance (Information Retrieval)
Lancaster, F. W.; And Others – Information Storage and Retrieval, 1972
An evaluation of the Epilepsy Abstracts Retrieval System (EARS) was performed. Searches were conducted on the on-line system and evaluated in terms of recall, precision, and general user satisfaction. A detailed analysis of factors affecting the success and failure of the on-line searches was carried out. (4 references) (Author/SJ)
Descriptors: Evaluation, Information Retrieval, Information Systems, Online Systems
Tell, Bjorn V. – Information Storage and Retrieval, 1971
Three experiments were made by a flexible machine search system to test the retrieval efficiency of searching free text and keywords. Results based upon relevance judgements of users indicate that titles and abstracts are good index material which can be used for machine searching without human indexing. (Author/SJ)
Descriptors: Automation, Indexing, Information Retrieval, Keywords
van Rijsbergen, C. J. – Information Storage and Retrieval, 1974
Reports the results of experiments in document clustering using three well-known test collections. (Author)
Descriptors: Classification, Cluster Grouping, Evaluation Methods, Information Retrieval
Rettenmayer, John W. – Information Storage and Retrieval, 1972
This study proposes and investigates file ordering and retrieval techniques which, it is hypothesized, will: (a) reduce the average cost of retrieving records which satisfy a query, and (b) increase the rate of retrieval in the initial portion of the response period. (8 references) (Author)
Descriptors: Cluster Grouping, Cost Effectiveness, Databases, Information Retrieval
Hansen, Inge Berg – Information Storage and Retrieval, 1973
A retrospective test search on one year of CA Condensates was carried out in order to calculate the costs per profile and to get an impression of how CA Condensates would suffice as a database for retrospective use. (11 references) (Author)
Descriptors: Cost Effectiveness, Information Retrieval, Information Storage, Information Systems
Sparck Jones, Karen – Information Storage and Retrieval, 1973
Retrieval performance with automatic term classifications for three test collections has been variable. This paper attempts to discover why. The real difference between the collections is in the separation of relevant from non-relevant documents. The separation is so poor that classification cannot be expected to succeed. (14 references)…
Descriptors: Automatic Indexing, Classification, Cluster Analysis, Databases
De Heer, T. – Information Storage and Retrieval, 1974
Use of syntactic trace as an access strategy for large files containing arbitrary languages for which thesaurus-based and multiple attribute search techniques are unsuitable. (LS)
Descriptors: Indexing, Information Retrieval, Information Storage, Mathematical Models
Minker, Jack; And Others – Information Storage and Retrieval, 1972
An evaluation of graph theoretical clusters of index terms which can be extracted from an automatically indexed document collection, and the effects of employing such clusters in automatic document retrieval are described. (19 references) (Author)
Descriptors: Automatic Indexing, Cluster Analysis, Data Processing, Information Retrieval
Jardine, N.; van Rijsbergen, C. J. – Information Storage and Retrieval, 1971
Introduced are information retrieval strategies based on automatic hierarchic clustering of documents. Cluster-based strategies are shown to be as effective as, and more efficient than, linear associative retrieval. (47 references) (Author/SJ)
Descriptors: Cluster Grouping, Information Retrieval, Organization
Humphrey, Susanne M. – Information Storage and Retrieval, 1975
Compares the ELHILL 2 and STAIRS programs with respect to on-line searching of the MEDLARS citation file by means of a chart showing the capabilities of the two programs. (Author/PF)
Descriptors: Computer Programs, Information Retrieval, Online Systems