Search (10 results, page 1 of 1)

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Date

22. 4.2007 10:07:51

LCSH

Indexing

Subject

Indexing

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Content

Enthält die Kapitel: Indexing principles, Indexing practice, Precoordinate indexes, Consistency of indexing, Quality of indexing, Abstracts: types and functions, Writing the Abstract, Evaluation aspects, Approaches used in indexing and abstracting services, Enhancing the indexing, On the indexing and abstracting of imaginative works, Indexing multimedia sources, Texte searching, Automatic indexing, automatic abstracting, and related procedures, Indexing and the Internet, The future of indexing and abstracting, exercises in indexing and abstracting

LCSH

Indexing
Indexing / Problems, exercises, etc.

Subject

Indexing
Indexing / Problems, exercises, etc.

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COMPASS

Indexing

Content

Enthält folgende Kapitel: Pre-coordinate indexes; consistency of indexing: quality of indexing; abstracts: types and functions, writing the abstract, natural language in information retrieval, automatic indexing. There are exercises in both indexing and abstracting procedures

LCSH

Indexing

Subject

Indexing
Indexing

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Content

Covers: indexing principles and practice; precoordinate indexes; consistency and quality of indexing; types and functions of abstracts; writing an abstract; evaluation theory and practice; approaches used in indexing and abstracting services; indexing enhancement; natural language in information retrieval; indexing and abstracting of imaginative works; databases of images and sound; automatic indexing and abstracting; the future of indexing and abstracting services

LCSH

Indexing
Indexing / Problems, exercises, etc.

Subject

Indexing
Indexing / Problems, exercises, etc.

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Abstract

Computer have been used in 2 areas of printed index production: to sort entries and fromat printed indexes, and to derive a series of index entries from a minimum intellectual input. Computer indexing enables more indexing terms to be used as well as weighted terms, links and roles. Interest in automatic indexing peaked in the mid-1960s and has since declined. Interest in machine-aided indexing concentrates on using the computer for on-line display or for indexing by extraction. Computers have also made possible the implementation of retrieval systems without indexing-free text systems. Considers future prospects and needs

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Abstract

F. W. Lancaster is known for his writing an the state of the art in librarylinformation science. His skill in identifying significant contributions and synthesizing literature in fields as diverse as online systems, vocabulary control, measurement and evaluation, and the paperless society have earned him esteem as a chronicler of information science. Equally deserving of repute is his own contribution to research in the discipline-his evaluation of the MEDLARS operating system. The MEDLARS study is notable for several reasons. It was the first large-scale application of retrieval experiment methodology to the evaluation of an actual operating system. As such, problems had to be faced that do not arise in laboratory-like conditions. One example is the problem of recall: how to determine, for a very large and dynamic database, the number of documents relevant to a given search request. By solving this problem and others attendant upon transferring an experimental methodology to the real world, Lancaster created a constructive procedure that could be used to improve the design and functioning of retrieval systems. The MEDLARS study is notable also for its contribution to our understanding of what constitutes a good index language and good indexing. The ideal retrieval system would be one that retrieves all and only relevant documents. The failures that occur in real operating systems, when a relevant document is not retrieved (a recall failure) or an irrelevant document is retrieved (a precision failure), can be analysed to assess the impact of various factors an the performance of the system. This is exactly what Lancaster did. He found both the MEDLARS indexing and the McSH index language to be significant factors affecting retrieval performance. The indexing, primarily because it was insufficiently exhaustive, explained a large number of recall failures. The index language, largely because of its insufficient specificity, accounted for a large number of precision failures. The purpose of identifying factors responsible for a system's failures is ultimately to improve the system. Unlike many user studies, the MEDLARS evaluation yielded recommendations that were eventually implemented.* Indexing exhaustivity was increased and the McSH index language was enriched with more specific terms and a larger entry vocabulary.

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Abstract

F.W. Lancaster's work has been immensely influential in library and information science. He has written on indexing and information system evaluation, and has been looked to as a pioneer in many areas. Here he describes precision and recall, the two most fundamental and widespread measures of information retrieval effectiveness.

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Abstract

An overview of levels and approaches in the evalution of knowledge-based systems is presented. There is a need for empirical studies using objective criteria in advance of completing the technical evaluation of such systems. A methodology for this type of evaluation developed for a particular knowledge-based indexing system is presented. It is suggested that the proposed study may serve as a model for the design of any evaluation in which the results of existing intellectual procedures are compared with results achieved when these procedures are aided by use of an appropriate expert system

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Footnote

Rez. in: JASIST 53(2002) no.4, S.321-322 (I. Fourie): "A substantial literature exists on artificial intelligence (AI) and expert systems in general, as well as in Library and Information Science (LIS). Many reports are over-confident and grossly exaggerate the power and potential of artificial intelligence (AI). This is especially true of the first phase of At, and to some extent also of the third phase that is stimulated by developments surrounding the Internet. The middle phase was mostly marked by disillusionment about the potential of Al and expert systems. The confusion around the promises made by AI and the lack of operational success, leaves managers of library and information services with the dilemma of distinguishing between worthwhile research reporting on operational projects and projects that exists only on paper or in the researchers' heads. It is very difficult to sieve between the two when working through the subject literature, and to distinguish between working technology/applications and wishful thinking. This might be one reason why working systems are sometimes ignored. According to Lancaster and Warner, library managers must also look much wider than the LIS literature to note new trends; this can, however, become a daunting task. Against this background the authors report on a study conducted with the support of the Special Libraries Association's Steven I. Goldspiel Memorial Research Grant. The objective of the study was to gain sufficient familiarity with the developments in Al and related technologies to make recommendations to the information service community on what can be applied, and what to expect in the near future. The intention therefore was to focus on systems that are actually operational, and systems that hold potential for the future. Since digital libraries seems an inevitable part of our future, applications concerning them features strongly in the final recommendations. The scope of AI in Library and Information Science depends on the interpretation of the concepts artificial intelligence and expert systems. "If a system has to `behave intelligently' (e.g. make inferences or learn from its mistakes) to qualify as having AI, few such systems exist in any application. On the other hand, if one accepts that a system exhibits AI if its does things that humans need intelligence to do, many more systems would qualify" (p. 107). One example is the field of subject indexing. The same would apply if a more relaxed definition of expert systems is applied as a system that "can help the non-expert perform some task at a level closer to that of an expert, whether or not all the essential components are in place" (p. 107). Most of the AI literature relevant to libraries falls in the field of expert systems. Lancaster and Warner identify (p. 6) expert systems as " a branch of artificial intelligence, even though very few expert systems exhibit true intelligence.""