The term IR may be considered a research field, but it may also be considered a research tradition (or rather a set of related traditions) based on some particular assumptions. In the first sense of the word is it about any approach (manual or mechanical) to organizing and searching "information". In the last sense of the word IR is one among a set of competing approaches to organizing and searching "information". Today is the term IR mostly associated with a set of particular research traditions (the Boolean, the Vector, and the Probabilistic tradition), why it seems out place when Stockwell (2000) in his book A History of Information Storage and Retrieval writes about encyclopedias and ignores the experimental traditions. Stockwell′s book is an example on how the term IR is used about the field rather than about the tradition.
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The term IR was introduced by Calvin Mooers in 1951, who defined it in this way: 数据挖掘工具
"Information retrieval is the name for the process or method whereby a prospective user of information is able to convert his need for information into an actual list of citations to documents in storage containing information useful to him. It is the finding or discovery process with respect to stored information. It is another, more general, name for the production of a demand bibliography. Information retrieval embraces the intellectual aspects of the description of information and its specification for search, and also whatever systems, technique, or machines that are employed to carry out the operation. Information retrieval is crucial to documentation and organization of knowledge". (Mooers, 1951, p. 25).
Van Rijsbergen writes: 数据挖掘研究院
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"Information retrieval is a wide, often loosely-defined term but in these pages I shall be concerned only with automatic information retrieval systems. Automatic as opposed to manual and information as opposed to data or fact. Unfortunately the word information can be very misleading. In the context of information retrieval (IR), information, in the technical meaning given in Shannon′s theory of communication, is not readily measured (Shannon & Weaver 1). In fact in many cases, one can adequately describe the kind of retrieval by simply substituting "document" for "information". Nevertheless, "information retrieval" has become accepted as a description of the kind of work published by Cleverdon, Salton, Spark Jones, Lancaster and others. A perfectly straightforward definition along this line is given by Lancaster 2: "Information retrieval is the term conventionally, though somewhat inaccurately, applied to the type of activity discussed in this volume. An information retrieval system does not inform (i.e. change the knowledge of) the user on the subject of his inquiry. It merely informs on the existence (or non-existence) and whereabouts of documents relating to his request". This specifically excludes Question-Answering systems as typified by Winograd 3 and those described by Minsky 4. It also excludes data retrieval systems such as used by, say, the stock exchange for on-line quotations. 数据挖掘论坛
. . . " (Van Rijsbergen, 1979, p. 1).
It is evident from the quotes by Mooers and Van Rijsbergen that the IR-tradition is related to a computer-based searching and experimenting in (mainly bibliographical or full-text) databases. Compared to the concept "Information seeking" it still has a connotation towards computer based retrieval, while information seeking has a broader connotation. 数据挖掘论坛
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D. A. Kemp argues that "knowledge retrieval" should substitute "information retrieval": 数据挖掘论坛
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"Knowledge, information and data and their representation. It can be useful to distinguish between knowledge and information and data; it is also difficult and contentious. Four points should be made. [First] Knowledge, information and data is what the systems to be discussed are for: by storing it in an organized manner, they are intended to enable it to be found when needed. Secondly, there is a spectrum of increased size and organization between data, where the units are quite small, through to knowledge, where the units are large and distinguished by their complex internal structure and relationships, and overlap with other units (Serebriakoff, 1986, D91). Meunier (1987, E44) presents a typology of levels of representation which is useful for the breath of its approach and its classification of relationships. Thirdly, "information" in the expression "information retrieval" is generally abused, because what is retrieved is not information, but bibliographic details of sources in which desired information potentially exists. Very many information retrieval systems are at best document retrieval systems, and more usually they are systems which retrieve surrogates for documents (see also Lancaster, 1979, A140, p. 13). Finally, although the expression knowledge retrieval is particularly associated with artificial intelligence and expert systems (smith, 1984, C78), it should not be forgotten that this is what cataloguers, indexers and bibliographers have been doing, and devising systems for, for many years. For further discussion, see Kemp (1974, A36) and McGarry (1977, E189." (Kemp, 1988, p. 3).
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Francis Miksa regards the traditional view within IR is a narrow view:
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"In this context, information is retrieved primarily in response to a clearly delineated decision-making process and seems to serve chiefly to fill a consciously estimated gap in the view the user has of a problem. This leads in turn to viewing retrieval systems as mechanisms that by definition must respond directly and with reasonable precision to a relative precise information request―to function, in short, as question-answer processes . . . intellectual knowledge appears to be characterized by a relatively unfocused sense of inquiry where the initial goal is not to find some particular informational answer or to fill some sort of reasonably anticipated informational gap, but rather to bring order to (or to re-order) an ill-formed mass of ideas or to map some vaguely arranged area of knowledge. Information retrieval in such situations takes on the character, then, of helping an inquirer think about what he or she appears to be interested in, and might be better conceived as an exploratory and game-like mechanism rather than a precise response mechanism". (Miksa, 1992, p. 240-241). 数据挖掘实验室
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Compare criticism by Julian Warner: query processing paradigm: 数据挖掘工具
"Two antithetical, if not always clearly distinguished, traditions can be detected in information retrieval system design and evaluation. The idea of query transformation, understood as the automatic transformation of a query into a set of relevant records, has been dominant in information retrieval theory. A contrasting principle of selection power has been valued in ordinary discourse, librarianship, and, to some extent, in practical system design and use". (Warner, 2002). 数据挖掘工具
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The two last quotes are also in accordance with this definition of IR:
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Information retrieval (IR) part of computer science which studies the retrieval of information (not data) from a collection of written documents. The retrieved documents aim at satisfying a user information need usually expressed in natural language. (Baeza-Yates & Ribeiro-Neto, 1999).
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Ian Ruthven finds that the classical model of IR-systems evaluation is obsolete: 数据挖掘工具
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"The classical model of IR system evaluation, initiated by the Cranfield experiments and currently manifest in the TREC programme, demonstrates very clearly its origins in the era of batch retrieval systems. The system is seen as taking well-defined input (a query or topic) and producing well-defined output (a list of documents). However, with modern interactive systems, that input-output model is clearly becoming more and more inadequate as a representation of the IR situation". (Ruthven, 1996).
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In the term "retrieval", the suffix "re" seems to indicate that something is "found again", implying that it has been identified at some earlier stage. This view may be correct when documents are represented in closed systems for specific purposes, but seems more problematic when items are retrieved by serendipity or by free text searching. In such cases are items found or identified, but not necessarily "retrieved".
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Literature:
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Baeza-Yates, R. & Ribeiro-Neto, B. (1999). Modern Information Retrieval. Boston, MA: Addison Wesley Longman Publishing Comp., Inc. Glossary: http://www.sims.berkeley.edu/~hearst/irbook/glossary.html 数据挖掘论坛
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Blair, D. C. (1990). Language and Representation in Information Retrieval. Amsterdam, Elsevier science publishers.
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Ellis, D. (1990). New Horizons in Information Retrieval. London: Library Association.
Ellis, D. (1996). Progress and problems in Information retrieval. London: Library Association.
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Kemp, D. A. (1988). Computer-based Knowledge Retrieval. Oxford: Aslib.
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Miksa, F. L. (1992). Library and information science: two paradigms. (Pp. 229-252) IN: Conceptions of Library and Information Science. Historical, empirical and theoretical perspectives. Ed. by Pertti Vakkari & Blaise Cronin. London: Taylor Graham.
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Mooers, C. N. (1951). Zatocoding applied to mechanical organization of knowledge. American Documentation, 2, 20-32.
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Robertson, S. E. (1977). Theories and Models in Information Retrieval. Journal of Documentation, 33(2), 126-148. 数据挖掘实验室
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Ruthven, I. (1996). MIRA: Evaluation Frameworks for Interactive Multimedia Information Retrieval Applications http://www.dcs.gla.ac.uk/mira/themes2.html 数据挖掘工具
Sparck Jones, K. (1992). Information retrieval. Vol. 1, pp. 684-690 IN: Encyclopedia of Artificial Intelligence. Vol. I-II. Ed. by Stuart C. Shapiro. New York: John Wiley & Sons.
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Stockwell , F. (2000). A History of Information Storage and Retrieval. Jefferson, North Caroling: McFarland & Company.
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van Rijsbergen, C. J. (1979). Information Retrieval. 2. ed. London: Butterworths. Online edition 1999. http://www.dcs.gla.ac.uk/~iain/keith/
Warner, J. (2002). Forms of labour in information systems. Information Research, 7(4) http://informationr.net/ir/7-4/paper135.html 数据挖掘交友
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Warner, J. (2004). A labor theoretic approach to information retrieval. http://www.sims.berkeley.edu:8000/courses/is296a-1/f04/summary.html 数据挖掘研究院
Wilson, P. (1978). Some Fundamental Concepts of Information Retrieval. Drexel Library Quarterly, 14, 10-24.
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See also: Information seeking; Latent semantic indexing; Probabilistic models of IR; Vector space model
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