The Effects and Limitations of Automated Text Condensing on Reading Comprehension Performance

• 成果类型: Article
• 署名作者: Morris, Andrew H.; Kasper, George M.; Adams, Dennis A.
• 署名单位: State University System of Florida; Florida State University; Texas Tech University System; Texas Tech University; University of Houston System; University of Houston
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.3.1.17
• 发表日期: 1992
• 页码: 17-35
• 关键词: information; systems; abstracts; retrieval; inference; issues; IMPACT

摘要

The optimal amount of information needed in a given decision-making situation lies somewhere along a continuum from not enough to too much. Ackoff proposed that information systems often hinder the decision-making process by creating information overload. To deal with this problem, he called for systems that could filter and condense data so that only relevant information reached the decision maker. The potential for information overload is especially critical in text-based information. The purpose of this research is to investigate the effects and theoretical limitations of extract condensing as a text processing tool in terms of recipient performance. In the experiment described here, an environment is created in which the effects of text condensing are isolated from the effects of message and individual recipient differences. The data show no difference in reading comprehension performance between the condensed forms and the original document. This indicates that condensed forms can be produced that are equally as informative as the original document. These results suggest that it is possible to apply a relatively simple computer algorithm to text and produce extracts that capture enough of the information contained in the original document so that the recipient can perform as if he or she had read the original. These results also identify a methodology for assessing the effectiveness of text condensing schemes. The research presented here contributes to a small but growing body of work on text-based information systems and, specifically, text condensing.