Number of found records: 9
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Nicholas, David; Huntington, Paul; Jamali, Hamid R |
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The Use, Users, and Role of Abstracts in the Digital Scholarly Environment |
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Journal of Academic Librarianship, 2007, Vol. 33 Issue 4, pp 446-453 |
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On line (04/2008) (Only UGR) |
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Utilizing transactional log data taken from digital journal libraries and attitudinal and demographic data derived from a questionnaire survey, the article pieces together evidence concerning the use, users, and role of abstracts in a digital environment. It shows that abstracts are used in large quantities, even when full-text viewing facilities are available. The `popularity' of abstracts is partly a function of how users navigate towards content in cyberspace, through search engines and gateways, and partly because they provide a quick and effective means of assessing relevance of content (AU) |
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Abstracts; electronic environment; use of abstract |
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DeSANTIS, Denny; LAUDATO, Nick |
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Management Information Systems |
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Pittsburgh: University, diciembre 1998 |
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On line ( 15/06/2004) |
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Basic concepts on information systems |
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information system; management information system; organizational culture |
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INGWERSEN, Peter |
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Cognitive perspectives of information retrieval interaction: elements of a cognitive ir theory. |
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Journal of documentation, 1996, vol.52, n.1, pp.3-50 |
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On line (06/05/2005) |
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Discusses the basic elements of a global cognitive theory for information retrieval (IR) interaction from a cognitive point of view. Within this framework are outlined the principles underlying the concept of polyrepresentation applied simultaneously to the user's cognitive space and the information space of IR systems (DB) |
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Cognitive Psychology; Information Retrieval; Knowledge representation; Information Needs; Information theory |
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JING, Hongyan |
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Using Hidden Markov Modelling to Decompose Human-Written Summaries. |
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Computational Linguistics, 2002, vol.28, n.4. |
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PDF |
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Professional summarizers often reuse original documents to generate summaries. The task of summary sentence decomposition is to deduce whether a summary sentence is constructed by reusing the original text and to identify reused phrases. Specifically, the decomposition program needs to answer three questions for a given summary sentence: (1) Is this summary sentence constructed by reusing the text in the original document? (2) If so, what phrases in the sentence come from the original document? and (3) From where in the document do the phrases come? Solving the decomposition problem can lead to better text generation techniques for summarization. Decomposition can also provide large training and testing corpora for extraction-based summarizers. We propose a hidden Markov model solution to the decomposition problem. Evaluations show that the proposed algorithm performs well. (AU) |
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sumarization; automation; |
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