Summarizing with LSA - Based Feedback 1 Developing Summarization Skills through the Use of LSA - Based Feedback

نویسندگان

  • Eileen Kintsch
  • Dave Steinhart
  • Gerry Stahl
چکیده

This paper describes a series of classroom trials during which we developed Summary Street, an educational software system that uses Latent Semantic Analysis to support writing and revision activities. Summary Street provides various kinds of feedback, primarily about whether a student summary adequately covers important source content and fulfills other requirements, such as length. The feedback allows students to engage in extensive, independent practice in writing and revising without placing excessive demands on teachers for feedback. We first discuss the underlying educational rationale, then present some results of the trials conducted with the system. We describe the collaborative process among researchers and teachers which enabled the development of a viable and supportive educational tool and its integration into classroom instruction.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Summarizing Opinions in Blog Threads

In this paper we present an approach to summarizing positive and negative opinions in blog threads. We first run a sentiment analysis system and consequently pass its output through a standard LSA-based text summarization system. Further on, we evaluate our approach and present the results obtained, which we believe are promising in the context of multi-document text summarization. Finally, we ...

متن کامل

Developing Summarization Skills through the Use of LSA-Based Feedback

This paper describes a series of classroom trials during which we developed Summary Street, an educational software system that uses Latent Semantic Analysis to support writing and revision activities. Summary Street provides various kinds of feedback, primarily about whether a student summary adequately covers important source content and fulfills other requirements, such as length. The feedba...

متن کامل

SUTLER: Update Summarizer Based on Latent Topics

This paper deals with our past and recent research in text summarization. We went from single-document summarization through multidocument summarization to update summarization. We describe the development of our summarizer which is based on latent semantic analysis (LSA). The classical LSA-based summarization model was improved by Iterative Residual Rescaling. We propose the update summarizati...

متن کامل

Content - based feedback 1 Supporting content - based feedback in online writing evaluation with LSA

This paper describes tests of an automated essay grader and critic that uses Latent Semantic Analysis. Several methods which score the quality of the content in essays are described and tested. These methods are compared against human scores for the essays and the results show that LSA can score as accurately as the humans. Finally, we describe the implementation of the essay grader/critic in a...

متن کامل

Text summarization using a trainable summarizer and latent semantic analysis

This paper proposes two approaches to address text summarization: modified corpus-based approach (MCBA) and LSA-based T.R.M. approach (LSA+T.R.M.). The first is a trainable summarizer, which takes into account several features, including position, positive keyword, negative keyword, centrality, and the resemblance to the title, to generate summaries. Two new ideas are exploited: (1) sentence po...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2000