Search (6 results, page 1 of 1)

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Source

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

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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

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Abstract

In 1985, an article by Blair and Maron described a detailed evaluation of the effectiveness of an operational full text retrieval system used to support the defense of a large corporate lawsuit. The following year Salton published an article which called into question the conclusions of the 1985 study. The following article briefly reviews the initial study, replies to the objections raised by the secon article, and clarifies several confusions and misunderstandings of the 1985 study

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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.

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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.