Abstracts produced using computer assistance

Abstract

Experimental subjects wrote abstracts of articles using a simplified version of the TEXNET abstracting assistance software. In addition to the full text, subjects were presented with either keywords or phrases extracted automatically. The resulting abstracts, and the times taken, were recorded automatically; some additional information was gathered by oral questionnaire. Selected abstracts produced were evaluated on various criteria by independent raters. Results showed considerable variation among subjects, but 37% found the keywords or phrases “quite” or “very” useful in writing their abstracts. Statistical analysis failed to support several hypothesized relations: phrases were not viewed as significantly more helpful than keywords; and abstracting experience did not correlate with originality of wording, approximation of the author abstract, or greater conciseness. Requiring further study are some unanticipated strong correlations including the following: Windows experience and writing an abstract like the author's; experience reading abstracts and thinking one had written a good abstract; gender and abstract length; gender and use of words and phrases from the original text. Results have also suggested possible modifications to the TEXNET software.

Features of DESCRIPTION META tags in public home pages

“…The average values for Simpson's l for descriptions were slightly lower than those observed in a previous study of abstracts produced with computer assistance [39], where the minimum was 0.0069 and the maximum 0.0233, with a mean of 0.0136, a standard deviation of 0.0033 and a median of 0.0136. If the short descriptions with values of zero are ignored, however, the average values are much more similar.…”

“…The mean proportion of description words found in the visible text showed a much greater range (100%) than that observed in experiments in which subjects wrote abstracts of scholarly articles [39], where the lowest proportion was 45%. The mean, however, was comparable to the proportions observed in author abstracts of the same documents (78%, 77%, 82%).…”

Joint Optimization of User-desired Content in Multi-document Summaries by Learning from User Feedback

“…Computer-assisted summarization. The majority of the existing computer-assisted summarization tools (Craven, 2000;Narita et al, 2002;Orǎsan et al, 2003;Orǎsan and Hasler, 2006) present important elements of a document to the user. Creating a summary then requires the human to cut, paste, and reorganize the important elements in order to formulate a final text.…”

Abstracts as orientation tools in a modular electronic environment

“…Automatic tools could be used e¬ectively, however, to support the human summarization process. A modular electronic environment lends itself well for further concretization of the idea of the 'abstractor's workbench' (Paice, Black, Johnson & Neal, 1994) or 'abstractor's assistant' (Craven, 2000): a system that, after generating a 'protosummary', would provide the author with tools to edit the proto-summary and thus to construct a satisfactory ¼nished summary. In this way, the new publication format would not only facilitate the retrieval and usage, but also the composition of electronic summaries.…”