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  • × author_ss:"Austin, D."
  1. Austin, D.: Development of a new general classification : a progress report (1969) 0.00
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  2. Austin, D.: ¬The development of PRECIS: a theoretical and technical history (1974) 0.00
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  3. Austin, D.: ¬The CRG research into a freely faceted scheme (1976) 0.00
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  4. Austin, D.: PRECIS in a multilingual context : Pt.1: PRECIS: an overview (1976) 0.00
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    Abstract
    The present paper is offered as the first of a series of articles in which PRECIS will be reviewed as a potential multi-lingual system, having in mind the obvious need, notably in a European context, for standard and language independent methods of subject analysis and document description. This first paper outlines the origins of PRECIS, and considers its use in English language indexing. A second paper will deal in general terms with the syntactical model which is used for producing PRECIS input strings and index entries. Later papers will then review the application of this model to indexing in, firstly, the Germanic languages (e.g. German and Danish), and, secondly, the Romance languages, illustrated by French.
    Type
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  5. Austin, D.: ¬The theory of integrative levels reconsidered as the basis of a general classification (1969) 0.00
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  6. Austin, D.; Digger, J.A.: PRECIS: The Preserved Context Index System (1977) 0.00
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  7. Austin, D.: Vocabulary control and information technology (1986) 0.00
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  8. Palmer, B.I.; Austin, D.: Itself an education : six lectures on classification, containing a continuation by Derek Austin entitled "Two steps forward..." (1971) 0.00
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  9. Austin, D.: PRECIS: Basic principles, functions and use (1984) 0.00
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  10. Austin, D.: How Google finds your needle in the Web's haystack : as we'll see, the trick is to ask the web itself to rank the importance of pages... (2006) 0.00
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    Abstract
    Imagine a library containing 25 billion documents but with no centralized organization and no librarians. In addition, anyone may add a document at any time without telling anyone. You may feel sure that one of the documents contained in the collection has a piece of information that is vitally important to you, and, being impatient like most of us, you'd like to find it in a matter of seconds. How would you go about doing it? Posed in this way, the problem seems impossible. Yet this description is not too different from the World Wide Web, a huge, highly-disorganized collection of documents in many different formats. Of course, we're all familiar with search engines (perhaps you found this article using one) so we know that there is a solution. This article will describe Google's PageRank algorithm and how it returns pages from the web's collection of 25 billion documents that match search criteria so well that "google" has become a widely used verb. Most search engines, including Google, continually run an army of computer programs that retrieve pages from the web, index the words in each document, and store this information in an efficient format. Each time a user asks for a web search using a search phrase, such as "search engine," the search engine determines all the pages on the web that contains the words in the search phrase. (Perhaps additional information such as the distance between the words "search" and "engine" will be noted as well.) Here is the problem: Google now claims to index 25 billion pages. Roughly 95% of the text in web pages is composed from a mere 10,000 words. This means that, for most searches, there will be a huge number of pages containing the words in the search phrase. What is needed is a means of ranking the importance of the pages that fit the search criteria so that the pages can be sorted with the most important pages at the top of the list. One way to determine the importance of pages is to use a human-generated ranking. For instance, you may have seen pages that consist mainly of a large number of links to other resources in a particular area of interest. Assuming the person maintaining this page is reliable, the pages referenced are likely to be useful. Of course, the list may quickly fall out of date, and the person maintaining the list may miss some important pages, either unintentionally or as a result of an unstated bias. Google's PageRank algorithm assesses the importance of web pages without human evaluation of the content. In fact, Google feels that the value of its service is largely in its ability to provide unbiased results to search queries; Google claims, "the heart of our software is PageRank." As we'll see, the trick is to ask the web itself to rank the importance of pages.
  11. Austin, D.: Differences between library classifications and machine-based subject retrieval systems : some inferences drawn from research in Britain, 1963-1973 (1979) 0.00
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    Source
    Ordering systems for global information networks. Proc. of the 3rd Int. Study Conf. on Classification Research, Bombay 1975. Ed. by A. Neelameghan
    Type
    a
  12. Austin, D.: ¬A proposal for an International Standard Object Numberworks (1999) 0.00
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    Abstract
    It is a fact that those involved with the humanities use visual resources for references in their work. Yet access to visual resources is no where near as certain or assured as print material. This is equally true for resources that may be discovered at a museum, an archive, in a slide collection, or on the Web. Inception of an International Standard Object Number, similar to International Standard Bibliographic Numbers for books and International Standard Serials Numbers for periodicals will advance accurate and timely access to visual resources. Unique numbers or codes which refer not only to the object but to any digital or non digital surrogate is desired by those whose interests lie in visual resources, digital objects or metadata. This paper discusses extant paradigms (ISBN, ISSN, ISMN, and the emerging ISAN) and models a procedure for assigning ISONs to objects and their surrogates. Resources requisite to the construction of the ISON are described, and a clear outline of the necessarily cooperative work ahead are discussed if an ISON can become a standard which will help in the discovery of visual resources in an open, shared environment
    Type
    a
  13. Austin, D.: ¬The exchange of subject information (1975) 0.00
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  14. Austin, D.: PRECIS: theory and practice (1984) 0.00
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  15. Austin, D.: ¬The new general faceted classification : an outline of the CRG scheme (1969) 0.00
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  16. Austin, D.; Sørensen, J.: PRECIS in a multilingual context : Pt.2: A linguistic and logical explanation of the syntax. (1976) 0.00
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    Abstract
    In this second paper in the series on PRECIS we set out to establish a theoretical model of the indexing operation to account for the growing empirical evidence that PRECIS can be applied successfully to the terms and phrases of more than one natural language (NL). For this purpose, the system is examined from two different but related viewpoints, the first linguistic and the second logical. In linguistic terms, the schema of role operators is related to certain features of NL which are regarded by linguists as language-independent, particular attention being paid to Chomsky's 1965 theory, the notion of deep cases, and the idea that roles, as used in an indexing language (IL) are related to deep cases in NL. It is realised that we should not rely too heavily on analogies between NL and IL, on the grounds that these two kinds of language have different structures and to some extent different functions, Consequently, the structure of a PRECIS string is also considered in terms of an alternative logic, and it is suggested that the order of terms in strings and entries, explained in the earlier paper through reference to the dual properties of context-dependency and one-toone relationships, is also amenable to a different but reinforcing explanation in terms of time-dependency. These two types of explanation, the linguistic and the logical, form the basis for a proposed theoretical model of the 'stages of indexing'. Finally, the authors consider the implications of this model for multilingual indexing.
    Type
    a
  17. Austin, D.; Digger, J.A.: PRECIS: The Preserved Context Index System (1985) 0.00
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    Abstract
    Probably the most interesting, original and controversial indexing system of the 1970s has been PRECIS (the Preserved Context Index System) developed by Derek Austin. It attracted such attention that the short courses given at the British National Bibliography offices in London -initiated as a means of teaching the staff of BNB who did subject indexing-were repeated all over the world, in the form of three-day or three-week sessions. A few fortunate non-BNB indexers were taken into London classes, taught by Austin and Digger, and had the advantage of a week's work with the regular staff theresomething that could not be done elsewhere. In addition, descriptions of the system were published from time to time as progress was made an the system itself and clarification or updating were needed. This article has been selected as an example of clarification. A second edition of the original 1974 Manual describing PRECIS appeared in early 1984, so the system may now be regarded as fully mature. PRECIS, which is the culmination of Austin's research for the Classification Research Group plus considerable additional input from the science of linguistics, is a highly sophisticated indexing system, deliberately created to be used with a computer. The motive behind it was that the indexer should do the brain work and the computer the nitty-gritty work of manipulating index terms. Chosen combinations and permutations are used as head words under strict rules to ensure that the context which defines the specific meaning of these words is always present, thus avoiding the ambiguity problem in indexing. The system also has classifi ation features, in part drawn from the Group's long interest in faceted classification. The actual index produces a large number of index entries, each carrying with it the basic context of the item being described. A weIl-defined terminology, in addition to contextdependency, is a feature of PRECIS. Role operators define the types of terms used and control the manipulations of the terms, which are originally entered as a string. The indexer is able to analyze and reduce to string form any document, process, or material that can be described in words, making it ideal for most audiovisual material.
    The system itself has two major aspects: - a syntactic approach in which relationships between terms are identified and tagged. Suitable algorithms for manipulation produce a very thorough index in which each head word is kept in context. - a semantic approach in which terminology is weIl defined by ensuring that the relationships of equivalence, hierarchy, and association are clearly established. Charts of relationships are created by inductive means (i.e., from the ground up). A special code for computer manipulation is used with each line of the string. This translates the string format into one that, with specially derived algorithms, can be used by the computer, to produce the actual index headings with all parts rotated by following the algorithm. The PRECIS system has been translated and utilized for languages other than English, notably French, German, and Danish. Modifications needed for idiosyncracies of each language have been made. Some, such as those modifications needed for German, have turned out to have usefulness with English as weIl. All in all, the system has such advanced indexing concepts that it provides a kind of indexing not possible before the computer came into common usage. Austin, who joined the staff of the British National Bibliography in 1963, is currently a member of the British Library staff. His early work included a NATO-sponsored research assignment for the Classification Research Group (q.v.). This, in turn, led to the development of PRECIS.
    Source
    Theory of subject analysis: a sourcebook. Ed.: L.M. Chan, et al
    Type
    a
  18. Austin, D.: Prospects for a new general classification (1969) 0.00
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    Abstract
    In traditional classification schemes, the universe of knowledge is brokeii down into self- contained disciplines which are further analysed to the point at which a particular concept is located. This leads to problems of: (a) currency: keeping the scheme in line with new discoveries. (b) hospitality: allowing room for insertion of new subjects (c) cross-classification: a concept may be considered in such a way that it fits as logically into one discipline as another. Machine retrieval is also hampered by the fact that any individual concept is notated differently, depending on where in the scheme it appears. The approach now considered is from an organized universe of concepts, every concept being set down only once in an appropriate vocabulary, where it acquires the notation which identifies it wherever it is used. It has been found that all the concepts present in any compound subject can be handled as though they belong to one of two basic concept types, being either Entities or Attributes. In classing, these concepts are identified, and notation is selected from appropriate schedules. Subjects are then built according to formal rules, the final class number incorporating operators which convey the fundamental relationships between concepts. From this viewpoint, the Rules and Operators of the proposed system can be seen as the grammar of an IR language, and the schedules of Entities and Attributes as its vocabulary.
    Type
    a
  19. Austin, D.; Sørensen, J.: PRECIS in a multilingual context : Pt.3: Multilingual experiments, proposed codes, and procedures for the Germanic languages. (1976) 0.00
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    Abstract
    PRECIS was introduced, mainly as an English language system, in the first paper in this series (1), and that account was followed by a generalised logicolinguistic explanation in the second (2). The present paper sets out to consider more practical matters of two kinds. Firstly, it describes some of the experiments in multilingual indexing which have been carried out already, noting in particular the lessons, leading to new procedures, drawn from these experiences. Secondly, the theoretical model proposed in the second paper, together with some of the new codes and procedures found to be necessary as the result of experiment with non-English languages, are related specifically to work in the Germanic languages.
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  20. Austin, D.: ¬The role of indexing in subject retrieval (1976) 0.00
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