-
Blake, C.: Text mining (2011)
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- Theme
- Data Mining
-
Benoit, G.: Data mining (2002)
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- Abstract
- Data mining (DM) is a multistaged process of extracting previously unanticipated knowledge from large databases, and applying the results to decision making. Data mining tools detect patterns from the data and infer associations and rules from them. The extracted information may then be applied to prediction or classification models by identifying relations within the data records or between databases. Those patterns and rules can then guide decision making and forecast the effects of those decisions. However, this definition may be applied equally to "knowledge discovery in databases" (KDD). Indeed, in the recent literature of DM and KDD, a source of confusion has emerged, making it difficult to determine the exact parameters of both. KDD is sometimes viewed as the broader discipline, of which data mining is merely a component-specifically pattern extraction, evaluation, and cleansing methods (Raghavan, Deogun, & Sever, 1998, p. 397). Thurasingham (1999, p. 2) remarked that "knowledge discovery," "pattern discovery," "data dredging," "information extraction," and "knowledge mining" are all employed as synonyms for DM. Trybula, in his ARIST chapter an text mining, observed that the "existing work [in KDD] is confusing because the terminology is inconsistent and poorly defined.
- Theme
- Data Mining
-
Trybula, W.J.: Data mining and knowledge discovery (1997)
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- Abstract
- State of the art review of the recently developed concepts of data mining (defined as the automated process of evaluating data and finding relationships) and knowledge discovery (defined as the automated process of extracting information, especially unpredicted relationships or previously unknown patterns among the data) with particular reference to numerical data. Includes: the knowledge acquisition process; data mining; evaluation methods; and knowledge discovery. Concludes that existing work in the field are confusing because the terminology is inconsistent and poorly defined. Although methods are available for analyzing and cleaning databases, better coordinated efforts should be directed toward providing users with improved means of structuring search mechanisms to explore the data for relationships
- Theme
- Data Mining
-
Bath, P.A.: Data mining in health and medical information (2003)
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- Abstract
- Data mining (DM) is part of a process by which information can be extracted from data or databases and used to inform decision making in a variety of contexts (Benoit, 2002; Michalski, Bratka & Kubat, 1997). DM includes a range of tools and methods for extractiog information; their use in the commercial sector for knowledge extraction and discovery has been one of the main driving forces in their development (Adriaans & Zantinge, 1996; Benoit, 2002). DM has been developed and applied in numerous areas. This review describes its use in analyzing health and medical information.
- Theme
- Data Mining
-
Chen, H.; Chau, M.: Web mining : machine learning for Web applications (2003)
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- Theme
- Data Mining
-
Enser, P.G.B.: Visual image retrieval (2008)
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- Date
- 22. 1.2012 13:01:26
-
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
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Belkin, N.J.; Croft, W.B.: Retrieval techniques (1987)
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- Source
- Annual review of information science and technology. 22(1987), S.109-145
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Smith, L.C.: Artificial intelligence and information retrieval (1987)
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- Source
- Annual review of information science and technology. 22(1987), S.41-77
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Warner, A.J.: Natural language processing (1987)
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- Source
- Annual review of information science and technology. 22(1987), S.79-108
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Grudin, J.: Human-computer interaction (2011)
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- Date
- 27.12.2014 18:54:22
-
Rader, H.B.: Library orientation and instruction - 1993 (1994)
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Hsueh, D.C.: Recon road maps : retrospective conversion literature, 1980-1990 (1992)
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- Cataloging and classification quarterly. 14(1992) nos.3/4, S.5-22
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Gabbard, R.: Recent literature shows accelerated growth in hypermedia tools : an annotated bibliography (1994)
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- Source
- Reference services review. 22(1994) no.2, S.31-40
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Buckland, M.K.; Liu, Z.: History of information science (1995)
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- Date
- 13. 6.1996 19:22:20
-
Haas, S.W.: Natural language processing : toward large-scale, robust systems (1996)
0.01
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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
-
Kim, K.-S.: Recent work in cataloging and classification, 2000-2002 (2003)
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- Date
- 10. 9.2000 17:38:22
