-
Enser, P.G.B.: Visual image retrieval (2008)
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- Date
- 22. 1.2012 13:01:26
-
Belkin, N.J.; Croft, W.B.: Retrieval techniques (1987)
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- Annual review of information science and technology. 22(1987), S.109-145
-
Smith, L.C.: Artificial intelligence and information retrieval (1987)
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- Annual review of information science and technology. 22(1987), S.41-77
-
Buckland, M.K.; Liu, Z.: History of information science (1995)
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- Abstract
- State of the art review of the historical development of information science as deemed to be covered by the particular interests of memebers of the American Society for Information Science, as defined as the representation, storage, transmission, selection, retrieval, filtering, and use of documents and messages. Arranges the references cited roughly according to the classification scheme used by Information Science Abstracts, and so uses the headings: background; information science; techniques and technology; information related behaviour; application areas; social aspects; education for information science; institutions; individuals; geographical areas; and conclusions
- Date
- 13. 6.1996 19:22:20
-
Haas, S.W.: Natural language processing : toward large-scale, robust systems (1996)
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- Abstract
- State of the art review of natural language processing updating an earlier review published in ARIST 22(1987). Discusses important developments that have allowed for significant advances in the field of natural language processing: materials and resources; knowledge based systems and statistical approaches; and a strong emphasis on evaluation. Reviews some natural language processing applications and common problems still awaiting solution. Considers closely related applications such as language generation and th egeneration phase of machine translation which face the same problems as natural language processing. Covers natural language methodologies for information retrieval only briefly
-
Hjoerland, B.; Kyllesbech Nielsen, L.: Subject access points in electronic retrieval (2001)
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- Theme
- Klassifikationssysteme im Online-Retrieval
Verbale Doksprachen im Online-Retrieval
-
Morris, S.A.: Mapping research specialties (2008)
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- Date
- 13. 7.2008 9:30:22
-
Fallis, D.: Social epistemology and information science (2006)
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- Date
- 13. 7.2008 19:22:28
-
Nicolaisen, J.: Citation analysis (2007)
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- Date
- 13. 7.2008 19:53:22
-
Metz, A.: Community service : a bibliography (1996)
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- Date
- 17.10.1996 14:22:33
-
Warner, A.J.: Natural language processing (1987)
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- Source
- Annual review of information science and technology. 22(1987), S.79-108
-
Grudin, J.: Human-computer interaction (2011)
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- Date
- 27.12.2014 18:54:22
-
Harter, S.P.; Hert, C.A.: Evaluation of information retrieval systems : approaches, issues, and methods (1997)
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- Abstract
- State of the art review of information retrieval systems, defined as systems retrieving documents a sopposed to numerical data. Explains the classic Cranfield studies that have served as a standard for retrieval testing since the 1960s and discusses the Cranfield model and its relevance based measures of retrieval effectiveness. Details sosme of the problems with the Cranfield instruments and issues of validity and reliability, generalizability, usefulness and basic concepts. Discusses the evaluation of the Internet search engines in light of the Cranfield model, noting the very real differences between batch systems (Cranfield) and interactive systems (Internet). Because the Internet collection is not fixed, it is impossible to determine recall as a measure of retrieval effectiveness. considers future directions in evaluating information retrieval systems
-
Bookstein, A.: Probability and Fuzzy-set applications to information retrieval (1985)
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-
Daniels, P.J.: Cognitive models in information retrieval : an evaluative review (1986)
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-
Ruthven, R.: Interactive information retrieval (2008)
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-
Foster, J.: Collaborative information seeking and retrieval (2006)
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-
Kantor, P.B.: Information retrieval techniques (1994)
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- Abstract
- State of the art review of information retrieval techniques viewed in terms of the growing effort to implement concept based retrieval in content based algorithms. Identifies trends in the automation of indexing, retrieval, and the interaction between systems and users. Identifies 3 central issues: ways in which systems describe documents for purposes of information retrieval; ways in which systems compute the degree of match between a given document and the current state of the query; amd what the systems do with the information that they obtain from the users. Looks at information retrieval techniques in terms of: location, navigation; indexing; documents; queries; structures; concepts; matching documents to queries; restoring query structure; algorithms and content versus concepts; formulation of concepts in terms of contents; formulation of concepts with the assistance of the users; complex system codes versus underlying principles; and system evaluation
-
Blair, D.C.: Information retrieval and the philosophy of language (2002)
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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.""
-
Schwarz, C.: Natural language and information retrieval : Kommentierte Literaturliste zu Systemen, Verfahren und Tools (1986)
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