Search (13 results, page 1 of 1)

Fallis, D.: Social epistemology and information science (2006) 0.02

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Date: 13. 7.2008 19:22:28

Houston, R.D.; Harmon, E.G.: Re-envisioning the information concept : systematic definitions (2002) 0.02

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Date: 22. 2.2007 18:56:23
22. 2.2007 19:22:13

Davenport, E.; Cronin, B.: Knowledge management : Semantic drift or conceptual shift? (2000) 0.01

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Date: 31. 7.2001 20:22:57

Bates, M.J.: Fundamental forms of information (2006) 0.01

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Date: 22. 3.2009 18:15:22

Meadows, J.: Understanding information (2001) 0.01

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Date: 15. 6.2002 19:22:01

Westbrook, L.: Information myths and intimate partner violence : sources, contexts, and consequences (2009) 0.01

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Date: 22. 3.2009 19:16:44

Atran, S.; Medin, D.L.; Ross, N.: Evolution and devolution of knowledge : a tale of two biologies (2004) 0.01

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Date: 23. 1.2022 10:22:18

Eiriksson, J.M.; Retsloff, J.M.: Librarians in the 'information age' : promoter of change or provider of stability? (2005) 0.01

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Date: 22. 7.2009 11:23:22

Raban, D.R.; Rafaeli, S.: ¬The effect of source nature and status on the subjective value of information (2006) 0.01

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Date: 22. 7.2006 15:09:35

Crane, G.; Jones, A.: Text, information, knowledge and the evolving record of humanity (2006) 0.01
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```
Abstract

Consider a sentence such as "the current price of tea in China is 35 cents per pound." In a library with millions of books we might find many statements of the above form that we could capture today with relatively simple rules: rather than pursuing every variation of a statement, programs can wait, like predators at a water hole, for their informational prey to reappear in a standard linguistic pattern. We can make inferences from sentences such as "NAME1 born at NAME2 in DATE" that NAME more likely than not represents a person and NAME a place and then convert the statement into a proposition about a person born at a given place and time. The changing price of tea in China, pedestrian birth and death dates, or other basic statements may not be truth and beauty in the Phaedrus, but a digital library that could plot the prices of various commodities in different markets over time, plot the various lifetimes of individuals, or extract and classify many events would be very useful. Services such as the Syllabus Finder1 and H-Bot2 (which Dan Cohen describes elsewhere in this issue of D-Lib) represent examples of information extraction already in use. H-Bot, in particular, builds on our evolving ability to extract information from very large corpora such as the billions of web pages available through the Google API. Aside from identifying higher order statements, however, users also want to search and browse named entities: they want to read about "C. P. E. Bach" rather than his father "Johann Sebastian" or about "Cambridge, Maryland", without hearing about "Cambridge, Massachusetts", Cambridge in the UK or any of the other Cambridges scattered around the world. Named entity identification is a well-established area with an ongoing literature. The Natural Language Processing Research Group at the University of Sheffield has developed its open source Generalized Architecture for Text Engineering (GATE) for years, while IBM's Unstructured Information Analysis and Search (UIMA) is "available as open source software to provide a common foundation for industry and academia." Powerful tools are thus freely available and more demanding users can draw upon published literature to develop their own systems. Major search engines such as Google and Yahoo also integrate increasingly sophisticated tools to categorize and identify places. The software resources are rich and expanding. The reference works on which these systems depend, however, are ill-suited for historical analysis. First, simple gazetteers and similar authority lists quickly grow too big for useful information extraction. They provide us with potential entities against which to match textual references, but existing electronic reference works assume that human readers can use their knowledge of geography and of the immediate context to pick the right Boston from the Bostons in the Getty Thesaurus of Geographic Names (TGN), but, with the crucial exception of geographic location, the TGN records do not provide any machine readable clues: we cannot tell which Bostons are large or small. If we are analyzing a document published in 1818, we cannot filter out those places that did not yet exist or that had different names: "Jefferson Davis" is not the name of a parish in Louisiana (tgn,2000880) or a county in Mississippi (tgn,2001118) until after the Civil War.

San Segundo, R.: ¬A new conception of representation of knowledge (2004) 0.01

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Date: 2. 1.2005 18:22:25

Benkowsky, J.; Bühring, B.; Georgy, U.; Linde, F.: Information pricing : the development of a product- and pricing concept for the research centre of the Public Library Cologne (2005) 0.01

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Date: 22. 7.2009 9:24:59

Hjoerland, B.: ¬The controversy over the concept of information : a rejoinder to Professor Bates (2009) 0.00

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Date: 22. 3.2009 18:13:27

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