-
Hartley, J.: Do structured abstracts take more space? : And does it matter? (2002)
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-
Endres-Niggemeyer, B.: Content analysis : a special case of text compression (1989)
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- Abstract
- Presents a theoretical model, based on the Flower/Hayes model of expository writing, of the process involved in content analysis for abstracting and indexing.
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Farrow, J.: All in the mind : concept analysis in indexing (1995)
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- Abstract
- The indexing process consists of the comprehension of the document to be indexed, followed by the production of a set of index terms. Differences between academic indexing and back-of-the-book indexing are discussed. Text comprehension is a branch of human information processing, and it is argued that the model of text comprehension and production debeloped by van Dijk and Kintsch can form the basis for a cognitive process model of indexing. Strategies for testing such a model are suggested
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Endres-Niggemeyer, B.; Maier, E.; Sigel, A.: How to implement a naturalistic model of abstracting : four core working steps of an expert abstractor (1995)
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- Abstract
- 4 working steps taken from a comprehensive empirical model of expert abstracting are studied in order to prepare an explorative implementation of a simulation model. It aims at explaining the knowledge processing activities during professional summarizing. Following the case-based and holistic strategy of qualitative empirical research, the main features of the simulation system were developed by investigating in detail a small but central test case - 4 working steps where an expert abstractor discovers what the paper is about and drafts the topic sentence of the abstract
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Rothkegel, A.: Abstracting from the perspective of text production (1995)
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- Abstract
- An abstract itself is a text which is subjected to general and specific conditions of text production. The goal - namely the forming of the abstract as a text - controls the whole process of abstracting. This goal oriented view contrasts to most approaches in this domain which are source text oriented. Production strategies are described in terms of text structure building processes which are reconstructed with methods of modelling in the area of text linguistics and computational linguistics. This leads to a close relationship between thr representation of the model and the resulting text. Gives examples in which authentic material of abstracts is analyzed according to the model. The model itself integrates 3 text levels which are combined and represented in terms of the writer's activities
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Endres-Niggemeyer, B.: ¬An empirical process model of abstracting (1992)
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-
Ou, S.; Khoo, C.; Goh, D.H.; Heng, H.-Y.: Automatic discourse parsing of sociology dissertation abstracts as sentence categorization (2004)
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- Abstract
- We investigated an approach to automatic discourse parsing of sociology dissertation abstracts as a sentence categorization task. Decision tree induction was used for the automatic categorization. Three models were developed. Model 1 made use of word tokens found in the sentences. Model 2 made use of both word tokens and sentence position in the abstract. In addition to the attributes used in Model 2, Model 3 also considered information regarding the presence of indicator words in surrounding sentences. Model 3 obtained the highest accuracy rate of 74.5 % when applied to a test sample, compared to 71.6% for Model 2 and 60.8% for Model 1. The results indicated that information about sentence position can substantially increase the accuracy of categorization, and indicator words in earlier sentences (before the sentence being processed) also contribute to the categorization accuracy.
- Content
- 1. Introduction This paper reports our initial effort to develop an automatic method for parsing the discourse structure of sociology dissertation abstracts. This study is part of a broader study to develop a method for multi-document summarization. Accurate discourse parsing will make it easier to perform automatic multi-document summarization of dissertation abstracts. In a previous study, we determined that the macro-level structure of dissertation abstracts typically has five sections (Khoo et al., 2002). In this study, we treated discourse parsing as a text categorization problem - assigning each sentence in a dissertation abstract to one of the five predefined sections or categories. Decision tree induction, a machine-learning method, was applied to word tokens found in the abstracts to construct a decision tree model for the categorization purpose. Decision tree induction was selected primarily because decision tree models are easy to interpret and can be converted to rules that can be incorporated in other computer programs. A well-known decision-tree induction program, C5.0 (Quinlan, 1993), was used in this study.
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Koltay, T.: ¬A hypertext tutorial on abstracting for library science students (1995)
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- Date
- 27. 1.1996 18:22:06
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Molina, M.P.: Documentary abstracting : toward a methodological approach (1995)
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- Abstract
- In the general abstracting process (GAP), there are 2 types of data: textual, within a particular framed trilogy (surface, deep, and rhetoric); and documentary (abstractor, means of production, and user demands). Proposes its development, the use of the following disciplines, among others: linguistics (structural, tranformational, and textual), logic (formal and fuzzy), and psychology (cognitive). The model for that textual transformation is based on a system of combined strategies with 4 key stages: reading understanding, selection, interpretation, and synthesis
-
Jizba, L.: Reflections on summarizing and abstracting : implications for Internet Web documents, and standardized library cataloging databases (1997)
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- Abstract
- Comments on the value of abstracts or summary notes to information available online via the Internet and WWW and concludes that automated abstracting techniques would be highly useful if routinely applied to cataloguing or metadata for Internet documents and documents in other databases. Information seekers need external summary information to assess content and value of retrieved documents. Examines traditional models for writers, in library audiovisual cataloguing, periodical databases and archival work, along with innovative new model databases featuring robust cataloguing summaries. Notes recent developments in automated techniques, computational research, and machine summarization of digital images. Recommendations are made for future designers of cataloguing and metadata standards
-
Palais, E.S.: Abstracting for reference librarians (1988)
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- Source
- Reference librarian. 1988, no.22, S.297-308
-
Hartley, J.; Sydes, M.: Which layout do you prefer? : an analysis of readers' preferences for different typographic layouts of structured abstracts (1996)
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- Source
- Journal of information science. 22(1996) no.1, S.27-37
-
Ward, M.L.: ¬The future of the human indexer (1996)
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- Date
- 9. 2.1997 18:44:22
-
Wan, X.; Yang, J.; Xiao, J.: Incorporating cross-document relationships between sentences for single document summarizations (2006)
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- Source
- Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006
-
Hartley, J.; Sydes, M.; Blurton, A.: Obtaining information accurately and quickly : are structured abstracts more efficient? (1996)
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- Source
- Journal of information science. 22(1996) no.5, S.349-356
