Search (12 results, page 1 of 1)

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Source

Information processing and management. 24(1988), S.349-371

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Abstract

Information retrieval - the retrieval, primarily, of documents or textual material - is fundamentally a linguistic process. At the very least we must describe what we want and match that description with descriptions of the information that is available to us. Furthermore, when we describe what we want, we must mean something by that description. This is a deceptively simple act, but such linguistic events have been the grist for philosophical analysis since Aristotle. Although there are complexities involved in referring to authors, document types, or other categories of information retrieval context, here I wish to focus an one of the most problematic activities in information retrieval: the description of the intellectual content of information items. And even though I take information retrieval to involve the description and retrieval of written text, what I say here is applicable to any information item whose intellectual content can be described for retrieval-books, documents, images, audio clips, video clips, scientific specimens, engineering schematics, and so forth. For convenience, though, I will refer only to the description and retrieval of documents. The description of intellectual content can go wrong in many obvious ways. We may describe what we want incorrectly; we may describe it correctly but in such general terms that its description is useless for retrieval; or we may describe what we want correctly, but misinterpret the descriptions of available information, and thereby match our description of what we want incorrectly. From a linguistic point of view, we can be misunderstood in the process of retrieval in many ways. Because the philosophy of language deals specifically with how we are understood and mis-understood, it should have some use for understanding the process of description in information retrieval. First, however, let us examine more closely the kinds of misunderstandings that can occur in information retrieval. We use language in searching for information in two principal ways. We use it to describe what we want and to discriminate what we want from other information that is available to us but that we do not want. Description and discrimination together articulate the goals of the information search process; they also delineate the two principal ways in which language can fail us in this process. Van Rijsbergen (1979) was the first to make this distinction, calling them "representation" and "discrimination.""

Source

Annual review of information science and technology. 37(2003), S.3-50

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Abstract

Information or Document Retrieval is the subject of this book. It is not an introductory book, although it is self-contained in the sense that it is not necessary to have a background in the theory or practice of Information Retrieval in order to understand its arguments. The book presents, as clearly as possible, one particular perspective on Information Retrieval, and attempts to say that certain aspects of the theory or practice of the management of documents are more important than others. The majority of Information Retrieval research has been aimed at the more experimentally tractable small-scale systems, and although much of that work has added greatly to our understanding of Information Retrieval it is becoming increasingly apparent that retrieval systems with large data bases of documents are a fundamentally different genre of systems than small-scale systems. If this is so, which is the thesis of this book, then we must now study large information retrieval systems with the same rigor and intensity that we once studied small-scale systems. Hegel observed that the quantitative growth of any system caused qualitative changes to take place in its structure and processes.

COMPASS

Information retrieval

LCSH

Information Retrieval

RSWK

Information Retrieval

Subject

Information retrieval
Information Retrieval
Information Retrieval

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Abstract

David Blair's article takes a comprehensive view of Knowledge Management, following its relationship to data or information management and its still promising possibilities.

Source

Journal of the American Society for Information Science and technology. 53(2002) no.13, S.xxxx-xxxx

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Source

Information processing and management. 26(1990), S.437-447

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Footnote

Vgl. auch : Salton, G.: Another look ... Comm. ACM 29(1986) S.S.648-656; Blair, D.C.: Full text retrieval ... Int. Class. 13(1986) S.18-23: Blair, D.C., M.E. Maron: Full-text information retrieval ... Inf. proc. man. 26(1990) S.437-447.

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Abstract

The test of retrieval effectiveness performed on IBM's STAIRS and reported in 'Communications of the ACM' 10 years ago, continues to be cited frequently in the information retrieval literature. The reasons for the study's continuing pertinence to today's research are discussed, and the political, legal, and commercial aspects of the study are presented. In addition, the method of calculating recall that was used in the STAIRS study is discussed in some detail, especially how it reduces the 5 major types of uncertainty in recall estimations. It is also suggested that this method of recall estimation may serve as the basis for recall estimations that might be truly comparable between systems

Source

Journal of the American Society for Information Science. 47(1996) no.1, S.4-22

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Abstract

This article examines the nature of Knowledge Management- how it differs from Data Management and Information Management, and its relationship to the development of Expert Systems and Decision Support Systems. It also examines the importance of Communities of Practice and Tacit Knowledge for Knowledge Management. The discussion is organized around five explicit questions. One: What is "knowledge"? Two: Why are people, especially managers, thinking about Knowledge Management? Three: What are the enabling technologies for Knowledge Management? Four: What are the prerequisites for Knowledge Management? Five: What are the major challenges for Knowledge Management?

Source

Journal of the American Society for Information Science and technology. 53(2002) no.12, S.1019-1028

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Abstract

With the growing focus on what is collectively known as "knowledge management", a shift continues to take place in commercial information system development: a shift away from the well-understood data retrieval/database model, to the more complex and challenging development of commercial document/information retrieval models. While document retrieval has had a long and rich legacy of research, its impact on commercial applications has been modest. At the enterprise level most large organizations have little understanding of, or commitment to, high quality document access and management. Part of the reason for this is that we still do not have a good framework for understanding the major factors which affect the performance of large-scale corporate document retrieval systems. The thesis of this discussion is that document retrieval - specifically, access to intellectual content - is a complex process which is most strongly influenced by three factors: the size of the document collection; the type of search (exhaustive, existence or sample); and, the determinacy of document representation. Collectively, these factors can be used to provide a useful framework for, or taxonomy of, document retrieval, and highlight some of the fundamental issues facing the design and development of commercial document retrieval systems. This is the first of a series of three articles. Part II (D.C. Blair, The challenge of commercial document retrieval. Part II. A strategy for document searching based on identifiable document partitions, Information Processing and Management, 2001b, this issue) will discuss the implications of this framework for search strategy, and Part III (D.C. Blair, Some thoughts on the reported results of Text REtrieval Conference (TREC), Information Processing and Management, 2002, forthcoming) will consider the importance of the TREC results for our understanding of operating information retrieval systems.

Source

Information processing and management. 38(2002) no.2, S.273-291

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Abstract

Recently, a detailed evaluation of a large, operational full-text document retrieval system was reported in the literature. Values of precision and recall were estimated usind traditional statistical sampling methods and blind evaluation procedures. The results of this evaluation demonstrated that the system tested was retrieving less then 20% of the relevant documents when the searchers believed it was retrieving over 75% of the relevant documents. This evaluation is described including some data not reported in the original article. Also discussed are the implications which this study has for how the subjects of documents should be represented, as well as the importance of rigorous retrieval evaluations for the furtherhance of information retrieval research

Footnote

Vgl.: Blair, D.C., M.E. Maron: An evaluation ... Comm. ACM 28(1985) S.280-299; Salton, G.: Another look ... Comm. ACM 29(1986) S.648-656; Blair, D.C., M.E. Maron: Full-text information retrieval ... Inf. Proc. Man. 26(1990) S.437-447.

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Source

Information processing and management. 38(2002) no.2, S.293-304

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Source

Information processing and management. 38(2002) no.3, S.445-451