Evaluation of Narrative and Expository Text Summaries Using Latent Semantic Analysis
نویسنده
چکیده
In this chapter I approach three automatic methods for the evaluation of summaries from narrative and expository texts in Spanish. The task consisted of correlating the evaluation made by three raters for 373 summaries with results provided by latent semantic analysis. Scores assigned by latent semantic analysis were obtained by means of the following three methods: 1) Comparison of summaries with the source text, 2) Comparison of summaries with a summary approved by consensus, and 3) Comparison of summaries with three summaries constructed by three language teachers. The most relevant results are a) a high positive correlation between the evaluation made by the raters (r= 0.642); b) a high positive correlation between the computer methods (r= 0.810); and c) a moderate-high positive correlation between the evaluations of raters and the second and third LSA methods (r= 0.585 and 0,604), in summaries from narrative texts. Both methods did not differ significantly in statistical terms from the correlation among raters when the texts evaluated were predominantly narrative. These results allow us to assert that at least two holistic LSA-based methods are useful for assessing reading comprehension of narrative texts written in Spanish.
منابع مشابه
Assessing short summaries with human judgments procedure and latent semantic analysis in narrative and expository texts.
In the present study, we tested a computer-based procedure for assessing very concise summaries (50 words long) of two types of text (narrative and expository) using latent semantic analysis (LSA) in comparison with the judgments of four human experts. LSA was used to estimate semantic similarity using six different methods: four holistic (summary-text, summary-summaries, summary-expert summari...
متن کاملUsing latent semantic analysis to grade brief summaries: some proposals
In this paper, we present several proposals in order to improve the LSA tools to evaluate brief summaries (less than 50 words) of narrative and expository texts. First, we analyse the quality of six different methods assessing essays that have been widely employed before (Foltz et al., 2000). The second objective is to analyse how new algorithms inspired by some authors (Denhière et al., 2007) ...
متن کاملUsing Latent Semantic Analysis to Grade Brief Summaries: 2
A study exploring texts at different academic levels. Abstract 26 27 In this study we propose an integrated method to automatically evaluate very brief 28 summaries (around 50 words) using the computational tool Latent Semantic Analysis 29 (LSA). The method proposed is based on a regression equation calculated with a corpus 30 of a hundred summaries (the training sample), and is validated on a ...
متن کاملMemory for narrative and expository text: independent influences of semantic associations and text organization.
The author examined memory for text in terms of the independent influences of semantic knowledge associations and text organization. Semantic associations were operationalized as the semantic relatedness between individual text concepts and the text as a whole and assessed with latent semantic analysis. The author assessed text organization by simulating comprehension with the construction inte...
متن کاملNew algorithms assessing short summaries in expository texts using latent semantic analysis.
In this study, we compared four expert graders with latent semantic analysis (LSA) to assess short summaries of an expository text. As is well known, there are technical difficulties for LSA to establish a good semantic representation when analyzing short texts. In order to improve the reliability of LSA relative to human graders, we analyzed three new algorithms by two holistic methods used in...
متن کامل